Psi Chi Journal Volumne 30.2 | Summer 2025

SUMMER 2025 | VOLUME 30 | ISSUE 2

ISSN: 2325-7342

Published by Psi Chi, The International Honor Society in Psychology ®

PSI CHI JOURNAL OF PSYCHOLOGICAL RESEARCH SUMMER 2025 | VOLUME 30, NUMBER 2

EDITOR

STEVEN V. ROUSE, PhD

Pepperdine University

Telephone: (310) 506-7959

Email: steve.rouse@psichi.org

ASSOCIATE EDITORS

JENNIFER L. HUGHES, PhD Agnes Scott College

STELLA LOPEZ, PhD University of Texas at San Antonio

TAMMY LOWERY ZACCHILLI, PhD Saint Leo University

ALBEE MENDOZA, PhD Delaware State University

KIMBERLI R. H. TREADWELL, PhD University of Connecticut

ROBERT R. WRIGHT, PhD Brigham Young University-Idaho

EDITOR EMERITUS

DEBI BRANNAN, PhD Western Oregon University

MANAGING EDITOR BRADLEY CANNON

DESIGNER

JANET REISS

EDITORIAL ASSISTANTS

EMMA SULLIVAN

ADVISORY EDITORIAL BOARD

GLENA ANDREWS, PhD RAF Lakenheath USAF Medical Center

AZENETT A. GARZA CABALLERO, PhD Weber State University

MARTIN DOWNING, PhD Lehman College

HEATHER HAAS, PhD University of Montana Western

ALLEN H. KENISTON, PhD University of Wisconsin–Eau Claire

MARIANNE E. LLOYD, PhD Seton Hall University

DONELLE C. POSEY, PhD Washington State University

LISA ROSEN, PhD Texas Women's University

CHRISTINA SINISI, PhD Charleston Southern University

ABOUT PSI CHI

Psi Chi is the International Honor Society in Psychology, founded in 1929. Its mission: "recognizing and promoting excellence in the science and application of psychology." Membership is open to undergraduates, graduate students, faculty, and alumni making the study of psychology one of their major interests and who meet Psi Chi’s minimum qualifications. Psi Chi is a member of the Association of College Honor Societies (ACHS), and is an affiliate of the American Psychological Association (APA) and the Association for Psychological Science (APS). Psi Chi’s sister honor society is Psi Beta, the national honor society in psychology for community and junior colleges.

Psi Chi functions as a federation of chapters located at senior colleges and universities around the world. The Psi Chi Headquarters is located in Chattanooga, Tennessee. A Board of Directors, composed of psychology faculty who are Psi Chi members and who are elected by the chapters, guides the affairs of the Organization and sets policy with the approval of the chapters.

Psi Chi membership provides two major opportunities. The first of these is academic recognition to all inductees by the mere fact of membership. The second is the opportunity of each of the Society’s local chapters to nourish and stimulate the professional growth of all members through fellowship and activities designed to augment and enhance the regular curriculum. In addition, the Organization provides programs to help achieve these goals including conventions, research awards and grants competitions, and publication opportunities.

JOURNAL PURPOSE STATEMENT

The twofold purpose of the Psi Chi Journal of Psychological Research is to foster and reward the scholarly efforts of Psi Chi members, whether students or faculty, as well as to provide them with a valuable learning experience. The articles published in the Journal represent the work of undergraduates, graduate students, and faculty; the Journal is dedicated to increasing its scope and relevance by accepting and involving diverse people of varied racial, ethnic, gender identity, sexual orientation, religious, and social class backgrounds, among many others. To further support authors and enhance Journal visibility, articles are now available in the PsycINFO®, EBSCO®, Crossref®, and Google Scholar databases. In 2016, the Journal also became open access (i.e., free online to all readers and authors) to broaden the dissemination of research across the psychological science community.

JOURNAL INFORMATION

The Psi Chi Journal of Psychological Research (ISSN 2325­7342) is published quarterly in one volume per year by Psi Chi, Inc., The International Honor Society in Psychology. For more information, contact Psi Chi Headquarters, Publication and Subscriptions, 651 East 4th Street, Suite 600, Chattanooga, TN 37403, (423) 756­2044. https://www.psichi.org; psichijournal@psichi.org

Statements of fact or opinion are the responsibility of the authors alone and do not imply an opinion on the part of the officers or members of Psi Chi.

Advertisements that appear in Psi Chi Journal do not represent endorsement by Psi Chi of the advertiser or the product. Psi Chi neither endorses nor is responsible for the content of third­party promotions. Learn about advertising with Psi Chi at https://www.psichi.org/Advertise

COPYRIGHT

Permission must be obtained from Psi Chi to reprint or adapt a table or figure; to reprint quotations exceeding the limits of fair use from one source, and/or to reprint any portion of poetry, prose, or song lyrics. All persons wishing to utilize any of the above materials must write to the publisher to request nonexclusive world rights in all languages to use copyrighted material in the present article and in future print and nonprint editions. All persons wishing to utilize any of the above materials are responsible for obtaining proper permission from copyright owners and are liable for any and all licensing fees required. All persons wishing to utilize any of the above materials must include copies of all permissions and credit lines with the article submission.

96 INVITED TEACHING RESOURCE: Beyond the Textbook: Psi Chi Journal Articles in Introductory Psychology Courses

Steven V. Rouse, Lexington K. Russell, and Ava E. Campbell Social Sciences Division, Pepperdine University

114 INVITED EDITORIAL: Involving Undergraduate Students in Programmatic Research: Social Media Use Among Brigham Young University–Idaho Students

Robert R. Wright Department of Psychology, Brigham Young University–Idaho

119 Effects of Controllability and Language on Stigma Toward Mental Illness

Claire E. Shaver, Kevin M. Summers, Gina A. Paganini, and E. Paige Lloyd* Psychology Department, University of Denver

129 Authoritative Parenting Moderates the Association Between Social Media Use and Self-Esteem in Young Adults

Lauren D. Adams1 and Patrick Cooper*2

1 Department of Applied Psychology, New York University.

2 Department of Arts and Sciences, Lynn University

142 Protected or Prone? Prescription Drug Misuse in Honors Program College Students

C. Veronica Smith*, Emily E. Haupt, and Lauren N. Jordan* Department of Psychology, University of Mississippi

150 Physiological Implications of Exclusion in Individuals With ADHD Symptomatology

Jaz E. Curtis, Sierra S. Swenson, Mariel Olsem, Annaka Scherf, and Rebecca J. Gilbertson* Department of Psychology, University of Minnesota Duluth

160 A Driving Simulator Experiment to Teach Experimental Design in an Undergraduate Psychology Research Methods Course

Forrest Toegel*, Mackenzie Baranski, and Cory Toegel* Department of Psychological Science, Northern Michigan University

(Continued on Next page)

Depression in Asian Americans: Does Generational Status and Acculturation Predict Severity and Type of Symptoms?

Anh N. Tang and Sharon M. Flicker * Department of Psychology, California State University, Sacramento

Intellectual Humility and Investigative Behaviors in Relation to Overclaiming of Knowledge

Emma E. Simpson and Katrina P. Jongman-Sereno* Department of Psychology, Elon University

Existential Concerns, Meaning, and College Adjustment Among Undergraduate College Students

William B. Monti1 and Rachel E. Dinero*2

1Department of Psychological and Brain Sciences & Department of Philosophy, Colgate University

2Department of Psychological and Brain Sciences, Colgate University

The Role of Client Preference for Therapeutic Alliance in Retention in Therapy

Madeline M. Breaux and Jennifer Zwolinski* Department of Psychological Sciences, University of San Diego

INVITED TEACHING RESOURCE:

Beyond the Textbook: Psi Chi Journal Articles in Introductory Psychology Courses

Steven V.

Rouse, Lexington

K. Russell,

and Ava

E. Campbell Social Sciences Division, Pepperdine University

Many faculty members teaching undergraduate courses incorporate empirical research articles into their classes, and a long line of research (beginning with Price, 1990) shows the pedagogical effectiveness of assigning readings from research reports. Because a student who reads journal articles develops a clearer understanding of the growth of generalizable knowledge, the ability to learn from primary sources is an important part of the educational and professional development of psychology students (Silvia et al., 2009). Nevertheless, professors often face numerous challenges when assigning primary sources to their students (Keith, 2013; Weiten & Houska, 2013). These challenges are especially noteworthy when teaching introductory psychology because many students are not prepared to understand a research report at such an early stage of their education (Griggs & Johnson, 2007). Because of these challenges, Landrum (2012) encouraged faculty to be mindful of several factors, such as the difficulty level of the article, cost, and recency of publication, and to consider online open­source materials when selecting primary source readings.

The Psi Chi Journal of Psychological Research is a valuable resource for introductory psychology professors for several reasons. First, all articles in all 30 volumes (to date) of the journal are publicly accessible to any reader, without requiring an account or subscription. Therefore, this journal represents an easy and economical addition to an introductory psychology course. Second, because this journal is the official publication of Psi Chi, articles can be submitted on any topic in contemporary psychology. Therefore, the journal’s breadth is as wide as a survey ­ style introductory psychology course. Third, because of the journal’s origin as an undergraduate research journal (though it currently serves as a publication venue for Psi Chi members at any stage of professional development), the journal remains committed to avoiding technical jargon specific to a precise subdiscipline of psychology. Therefore, a professor can have confidence that the readings will be accessible to students enrolled in an introductory psychology course.

To facilitate research literacy activities for introductory

psychology courses, our team searched the last five volumes of Psi Chi Journal, with an eye toward articles relevant to the chapters typically included in a standard Introduction to Psychology textbook (e.g., biological psychology, cognitive psychology, sensation and perception, memory). In the following pages, we provided reference information for each article, along with a slightly revised version of the abstracts (e.g., italicized terms, changing from first­person pronouns to third­person pronouns). Next, we defined key terms that might not be known in the general population. Then, we provided questions that an instructor could use in class to generate discussions and to help students develop an understanding of the basic structure of a research article. The first question for each article focuses on the primary findings of previous research, which will help students understand the purpose of a Literature Review section. The second question asks students to consider the specific reason the researchers conducted the study, generally drawing from the transitional section between the Literature Review and the Methods section. In the third question, the students are asked to discuss specific aspects of the research methodology, drawn from the Methods section. The fourth question examines the basic findings of the research as reported in the Results section, though keeping in mind the limited statistical knowledge most introductory students possess. Finally, the fifth question focuses on the Discussion section, exploring the implications of the research in light of the previous research.

We hope this resource proves to be useful for introductory psychology professors as they incorporate journal articles as primary sources. Please let us know if you have feedback so we can consider an updated version with new journal articles in the coming years.

References

Griggs, R. A., & Jackson, S. L. (2007). Classic articles as primary source readings in introductory psychology. Teaching of Psychology, 34(3), 181–186. https://doi.org/10.1080/00986280701498582

Keith, K. D. (2015). Designing the psychology course: Syllabus, readings, and assignments. In D. S. Dana (Ed.) Oxford handbook of undergraduate psychology education Oxford University Press.

Landrum, E. R. (2012). Selection of textbooks or readings for your course. In B. M. Schwartz and R. R. Gurung (Eds.), Evidence-based teaching for higher

SUMMER 2025

PSI CHI JOURNAL OF PSYCHOLOGICAL RESEARCH

education American Psychological Association.

Price, D. W. W. (1990). A model for reading and writing about primary sources: The case of introductory psychology. Teaching of Psychology, 17(1), 48–53. https://doi.org/10.1207/s15328023top1701_12

Silvia, P. J., Delaney, P. F., & Marcovitch, S. (2009). Primary sources: Finding, reading, and understanding journal articles. In P. J. Silvia, P. F. Delaney, & S. Marcovitch (Eds.), What psychology majors could (and should) be doing: An informal guide to research experience and professional skills (pp. 69–80). American Psychological Association. Weiten, W., & Houska, J. A. (2015). Introductory psychology: Unique challenges

and opportunities. In D. S. Dana (Ed.), Oxford handbook of undergraduate psychology education. Oxford University Press.

Author Note

Steven V. Rouse https://orcid.org/0000­0002­1080­5502

Lexington K. Russell https://orcid.org/0009­0005­9843­4150

Ava E. Campbell https://orcid.org/0000­0003­1511­4070 Correspondence concerning this manuscript should be addressed to Steven V. Rouse, Pepperdine University, Malibu, CA 90263. Email: steve.rouse@pepperdine.edu

Biological Psychology

Title:

The Effects of Hormonal Contraception on Auditory Emotional Memory

Authors: Jessica Simonson, Courtney A. Durdle, and Michael B. Miller

Volume: 28

Issue: 4

Page Numbers: 264–274

Direct Link: https://doi.org/10.24839/2325-7342.JN28.4.264

Abstract (Revised): Emotional episodic memory is an important cognitive mechanism that has been extensively studied; however, auditory emotional memory in particular has yet to be thoroughly understood. In addition, sex hormones have been found to affect brain structure and regulate regions of the brain that support higher-order cognitive functions. Considering the global usage of oral hormonal contraceptive pills, it is vitally important to investigate the effects of oral contraceptives on executive function, including memory. The aim of the present study was to investigate the extent to which oral contraceptives influence recall for an emotional auditory episodic memory compared to a neutral memory. Ninety participants (45 on an oral contraceptive and 45 naturally cycling) performed a free recall task for an emotional and a neutral auditory story, and their recollections were categorized into general and detail elements and rated for accuracy. Recall accuracy for an emotional or neutral auditory story was not different between women on oral hormonal contraceptives and women who were naturally cycling; however, both groups of women recalled more information regarding the neutral story compared to the emotional story. These findings inform how the use of hormonal contraceptive pills, combined with high emotional valence, may impact the content and accuracy of recalled episodic events.

Key Terms:

Episodic memory: Information about events someone has personally experienced, usually reported as a story. Example: the memory of your last birthday.

Sex hormones: Hormones, such as estrogen or testosterone, that affect sexual development or reproduction.

Free recall task: In this task, a participant recalls a list of items in any order. They are then prompted to recall the items in any order.

Emotional valence: The degree to which an emotion is considered pleasant or unpleasant.

Question 1 (Understanding background):

How might sex hormones, taken in the form of an oral hormonal contraceptive pill, influence one’s memory of emotional personal events?

Question 2 (Understanding purpose):

Despite the high popularity of the contraceptive pill method, research on the effects of this drug on the cognitive health of women is “relatively limited.” Why might this drug be an uncommon topic of research?

Question 3 (Understanding method):

Between the two auditory stimuli, participants answered demographic questions (regarding age, gender, sex at birth, race/ethnicity, etc). Why would the researchers have intentionally placed a “break” between the “emotional” and “neutral” audios?

Question 4 (Understanding results):

What were the results, and did these results support the researchers’ hypothesis?

Question 5 (Implications for life):

Previous research has indicated differences in recall between emotional and neutral visual stimuli (comparing women on hormonal contraceptives and those naturally cycling). Why would it be important to study the recall of auditory stimuli? What can we learn by seeing differences in recall between visual and auditory stimuli?

States of Consciousness

Title: Does Life Satisfaction Mediate the Relationship Between Mood and Daydreaming Frequency?

Authors: Ryan F. Tudino, Nicole L. Mowry, and William A. Jellison

Volume: 25

Issue: 2

Page Numbers: 90–97

Direct Link: https://www.psichi.org/resource/resmgr/journal_2020/25_2_tudino.pdf

Abstract (Revised): This study examined whether life satisfaction is the pathway between positive mood and daydreaming frequency. Two nonexperimental studies were conducted in which participants completed a questionnaire that assessed their positive mood, life satisfaction, and frequency of daydreaming. In Study 1, correlations were observed between positive mood and life satisfaction, life satisfaction and daydreaming frequency, and positive mood and daydreaming frequency. However, the proposed mediational model, that life satisfaction is the pathway between positive mood and daydreaming frequency, was not supported because the negative relationship between positive mood and daydreaming frequency remained statistically significant when life satisfaction was added to the regression equation. Study 2 aimed to increase the reliability and generalizability of Study 1. Results from Study 2 also did not support the mediational role of life satisfaction. However, the results of Study 2 also demonstrated a negative relationship between positive mood and daydreaming frequency, even when life satisfaction was included in the regression equation.

Key Terms:

Life Satisfaction: The degree to which someone perceives life as plentiful, rich, or of high quality.

Mediation Model: A model that tests whether life satisfaction mediates, or could account for, the relationship between positive mood and daydreaming frequency.

Question 1 (Understanding background):

Daydreaming, in particular maladaptive daydreaming, may aid in the creation of a negative reinforcement loop. How would you explain this phenomenon in your own words? Why might this pattern be dangerous?

Question 2 (Understanding purpose):

How does research indicate that mood, life satisfaction, and daydreaming frequency are related? Do these correlations tend to be positive or negative, and why?

Question 3 (Understanding method):

College students participated in Study 1. Adults were recruited for Study 2 using an online survey platform called MTurk. College students are often research subjects, although the population often does not represent the general population. Why would it be important to get a diverse sample of adults? In other words, why is a population of college students considered not to be representative?

Question 4 (Understanding results):

This study did not find any statistically significant relationships between life satisfaction and daydreaming frequency. However, there were slight positive trends for adults postcollege once life satisfaction was calculated as a factor, compared with a slight negative trend for college students in that same calculation. What would this difference in life stage indicate, based on this result?

Question 5 (Implications for life):

College students may experience guilty-dysphoric daydreaming more frequently than other adult demographics, which involves ruminating on a past or future event. However, postcollegiate adults daydream proactively more frequently. These daydreams involve problem-solving and planning for one’s future. In a clinical setting, how could therapists use the frequency and style of daydreaming to aid in a client’s treatment?

Sensation and Perception

Title: Role of Social Gaze on Visual Search in an Eye-Tracking Paradigm

Authors: Jonathan K. Kroeger, Erin A. Conway, and Ralph G. Hale

Volume: 28

Issue: 2

Page Numbers: 142–148

Direct Link: https://doi.org/10.24839/2325-7342.JN28.2.142

Abstract (Revised): Gaze cueing refers to the natural inclination to direct one’s gaze in the direction of another’s gaze. This can be used in visual search tasks to facilitate or interfere with the search. Here, we examined the interaction between three gaze cue conditions (congruent, incongruent, and neutral) and a search task using letter arrays. Congruent cues had a gaze cue looking at the target, incongruent cues had a gaze cue looking away from the target, and neutral cues had a gaze cue looking straight ahead. An eye tracker was used to measure search task completion times. For all conditions, participants fixated on a target stimulus in the middle of the screen to begin the trial. The target disappeared. Then the gaze cue appeared, followed by the search array. Participants then had to locate the target. The researchers expected completion times to be shortest for congruent cues and longest for incongruent cues, with neutral cues somewhere in the middle. Trials were randomized between the three conditions. They found a significant impact of gaze cueing on this search task. Pairwise comparisons found significant differences between congruent and incongruent conditions, and between neutral and congruent conditions. Together, these results supported the hypothesis; congruent gaze cueing facilitated visual search whereas incongruent gaze and neutral gaze failed to assist visual search. These findings provide a firmer understanding of the interactions between gaze cueing and visual search paradigms.

Key Terms:

Gaze Cueing: The innate desire to angle a person’s gaze in the same direction of another person’s gaze.

Visual Search Task: When individuals are given the task to find certain objects in a variety of assigned conditions.

Eye Tracking: This technology allows for the measurement of an individual’s specific eye movements as they are tracked during the completion of a task.

Question 1 (Understanding background):

In a visual search task, participants find target objects in a variety of conditions. What might make identifying a target object in this task easier, or more difficult?

Question 2 (Understanding purpose):

Why do we use “gaze cueing?” Would you consider this phenomenon to be an important part of social communication? Why or why not?

Question 3 (Understanding method):

In this study, the gaze cue used was a yellow smiley face, “looking” in various directions. Why is this effective? In other words, why are humans so quick to recognize faces?

Question 4 (Understanding results):

Congruent gaze cues significantly reduced search time, compared to neutral and incongruent gaze cues. However, the search times for neutral and incongruent conditions were not significantly different. What might this suggest?

Question 5 (Implications for life):

Children diagnosed with autism spectrum disorder may have difficulty with some socially learned cues, such as eye gaze alteration. How might researchers expand upon this study to further understand these cognitive differences?

Learning

Title: How Perceptions of Obstacles, Stress, and Different Mindsets May Impact a Student’s Self-Beliefs

Authors: Kristin P. Rullman, Samantha L. D’Anna, Lauren A. Jacobs, Kristina R. Jacobs, and William A. Jellison

Volume: 27

Issue: 2

Page Numbers: 105–112

Direct Link: https://www.psichi.org/resource/resmgr/journal_2022/27_2_Rullman.pdf

Abstract (Revised): The current study explored how the mediational model of perceived task complexity, academic stress, and self-efficacy is moderated by cognitive mindset. College students completed self-report measures of task complexity, academic stress, self-efficacy, and cognitive mindset. Results demonstrated that academic stress is a mediator between task difficulty and self-efficacy for students with a fixed mindset, but not for students with a growth mindset. There was a significant indirect effect at the mean of the moderator, a significant indirect effect at one standard deviation below the mean of the moderator, but no significant effect at one standard deviation above the mean. An implication is that college students may still benefit from growth mindset interventions even at a later stage in their academic careers. It can be helpful to make students aware of their cognitive mindset disposition so they can better handle their perceptions of difficulty and in times of stress. Mindset interventions should be explored in future research and implemented in school and university settings.

Key Terms:

Mediational model: An analysis that seeks to identify the mechanism underlying an observed relationship between an independent variable and a dependent variable, via the inclusion of a third explanatory variable (known as a mediating variable).

Moderator: A third variable affecting the strength of the relationship between two other variables.

Fixed mindset: One views intelligence, abilities, and talents as inherently stable and unchangeable over time.

Growth mindset: One views intelligence, abilities, and talents as learnable and capable of improvement through effort.

Self-efficacy: The extent to which one believes in their abilities to complete a task.

Question 1 (Understanding background):

Increased levels of stress generally lead to increased amounts of errors when completing a task. Why does stress have a connection to performance?

Question 2 (Understanding purpose):

Why would a “growth mindset” benefit students, compared to the presence of a “fixed mindset?”

Question 3 (Understanding method):

This study collected information from students through online surveys. Several items were reverse-coded, meaning that some items are “opposite” or changed from positive to negative statements. What would be the benefits of reverse-coding these items?

Question 4 (Understanding results):

This study concluded that academic stress is a mediator between task difficulty and self-efficacy for students with a fixed mindset, but not for students with a growth mindset. Using the definition of a “mediation model” above, how would you describe these results in your own words?

Question 5 (Implications for life):

Growth mindset interventions may not only be effective for middle school or high school students but for higher-education students as well. How could universities implement this knowledge to benefit students?

Cognition and Intelligence

Title: Psychological and Behavioral Predictors of Procrastination in Undergraduates

Authors: Bradley B. Gregory, Megan Golson, and McKay Larsen

Volume: 28

Issue: 1

Page Numbers: 52–65

Direct Link: https://doi.org/10.24839/2325-7342.JN28.1.52

Abstract (Revised): Utilizing previous work in personality theory, implicit theory of intelligence, goal orientation, and self-efficacy theory, the researchers conducted an exploratory study to identify predictors of general procrastination tendencies among undergraduates. They analyzed a sample of 267 undergraduate students from introductory psychology courses at a public rural university. Regression analysis identified four significant predictors and nine additional significant correlates, seven of which were significant. Positive predictors included growth mindset beliefs and academic entitlement beliefs. Negative predictors included conscientiousness and college student efficacy beliefs. These findings are consistent with previous work and further support the roles and directional influences of conscientiousness, college student efficacy beliefs, and implicit theory of intelligence beliefs on procrastination, and add to the growing literature on academic entitlement beliefs.

Key Terms:

Procrastination: A tendency to delay tasks without the need to do so.

Growth Mindset: Viewing intelligence, abilities, and talents as learnable and capable of improvement through effort; the opposite is a fixed mindset.

Academic Entitlement: A natural tendency to embody an expectation of academic success without assuming personal responsibility to achieve said success.

Conscientiousness: Considered a dimension in the five-factor personality model that measures the degree to which someone is organized, responsible, and hardworking.

Question 1 (Understanding background):

“Academic entitlement beliefs” can be defined as a propensity to possess an expectation of academic success without having to assume personal responsibility to achieve this success. How may social media and a growing consumer mindset have coincided with or contributed to the increase of these beliefs over recent generations?

Question 2 (Understanding purpose):

Although many studies have examined the consequences of procrastination, few have explored predictors or causes of procrastination. Why might this be?

Question 3 (Understanding method):

Social desirability bias can occur when respondents to a survey answer questions in ways they think will be viewed favorably by others. How could the researchers have limited the impact of social desirability bias in this study on procrastination?

Question 4 (Understanding results):

The results of this study indicate that the behavioral variable of daily social media did not significantly predict procrastination, but it did significantly correlate with procrastination. Why would this result be significant? Could there be another direct effect between social media and procrastination?

Question 5 (Implications for life):

Considering that the elements of academic entitlement and conscientiousness may both impact procrastination tendencies, how could students practically apply these results to their study habits?

Memory

Title: When Hints Hurt Memory: The Influence of the Number of Part-Set Cues on Free Recall

Authors: Deniz Akpinar, Vaughan Bamford, Sara Martinez Guzman, Tracey Nassuna, Madison Stevens, and Matthew R. Kelley

Volume: 28

Issue: 1

Page Numbers: 46–51

Direct Link: https://doi.org/10.24839/2325-7342.JN28.1.46

Abstract (Revised): The present study explored the effects of part-set cues on retention in a free recall task across five experiments. In the part-set cueing literature, researchers typically provide half of the to-be-remembered items as cues during the test; accordingly, little is known about the effect of the number of part-cues on retention, particularly when very few or very many cues are presented at the test. These experiments examined the effects of very few cues (2, 3, 4, 5, and 6 cues), half cues (15), and very many cues (25, 27, 28, and 29 cues) out of a list of 30 words. Put differently, the percentage of part-set cues in the Very Few Cues condition ranged from 7–20% of the list, the Half Cues condition was 50% of the list, and the Very Many Cues condition ranged from 83–97% of the list. The Very Few Cues conditions demonstrated null effects (all ps > .26), which suggests that there might be a minimum percentage of cues required before part-set cueing influences memory performance. In contrast, significant part-set cueing impairment occurred in all conditions where at least half of the cues were present (all ps < .03, except one marginally significant, p = .06, when comparing the 0 vs. 27 cue conditions). Generally, these results are consistent with predictions derived from the retrieval strategy disruption hypothesis (Basden & Basden, 1995).

Key Terms:

Part-Set Cueing: In a memory study, a list of words is presented for a participant to learn. Later, the participants are given cues by being told some of the words from the list.

Retrieval Strategy Disruption Hypothesis: If each person develops their own strategy for learning a list, their ability to recall the list might actually be disrupted if the reminders they are provided do not fit the strategy they used to remember the list in the first place.

Free Recall: A task that measures memory by asking participants to recall information in any order that was previously studied.

Question 1 (Understanding background):

Part-set cues commonly lead to impairment (poorer performance) on a free-recall memory test. However, part-set cues can sometimes lead to facilitation (improved performance) on memory tasks. What would make part-set cues more helpful or harmful?

Question 2 (Understanding purpose):

This study varies the number of part-set cues on free recall tasks. Make a few predictions: What percentage of part-set cues would need to appear before impairment occurs? Will impairment increase as the percentage of part-set cues increases?

Question 3 (Understanding method):

Participants completed the recall task online. The researchers decided to count typos of the presented words as “correct,” as long as two raters agreed that the word’s identity was clear. Why would it be important to get different perspectives on the word's identity?

Question 4 (Understanding results):

Statistical analyses indicate that part-set cueing did not have effects when the amount of cues was low (7–20% of the list). What does this result suggest about the amount of cues that need to be present before impairment of memory becomes evident?

Question 5 (Implications for life):

How could a well-meaning teacher, who tends to give hints on exams, utilize this research to benefit students on exams without impairing their memory?

Lifespan Development

Title: Creativity and Executive Function in School-Age Children: Effects of Creative Coloring and Individual Creativity on an Executive Function Sorting Task

Authors: Katherine C. Crenshaw and Stephanie E. Miller

Volume: 27

Issue: 1

Page Numbers: 81–90

Direct Link: https://www.psichi.org/resource/resmgr/journal_2022/27_1_Crenshaw.pdf

Abstract (Revised): This study examined the relationship between executive function (EF) and creativity and whether a creative manipulation related to free coloring or coloring task-relevant materials would impact EF performance. Participants also completed a variety of EF measures. Although they failed to find a relationship between creativity and EF measures, they found evidence to suggest the effects of a creative color manipulation differed by individual differences in creativity. Those who were low in certain creative components like the ability to switch between categories, generate a number of unique ideas, and originality seemed to perform better when allowed to freely color compared to other conditions. Those who performed higher in creative measures generally did not benefit from a creativity manipulation before the task. This suggests that a more nuanced examination of the relationship between creativity and EF considering possible experimental manipulations, multiple components, and individual differences may be useful in understanding the relationship between these two constructs.

Key Terms:

Executive Function (EF): Higher-order processes of cognition that are responsible for various skills and abilities, such as communicating information and regulating one’s emotions.

Creativity: The ability to develop something originally through a body of work, knowledge, or other techniques.

Creative Manipulation: A way to increase one’s creativity, through the stimulation of the prefrontal cortex, through interventions or activities such as free coloring that is associated with art-structured tasks.

Question 1 (Understanding background): Executive function develops significantly during the transition between early childhood and adolescence. The article lists a few interventions involving physical activity as positively affecting executive function development (tae-kwondo and yoga). What are some other examples of activities that would aid EF maturation? Think about your childhood experiences throughout that age range.

Question 2 (Understanding purpose): How do creative activities (such as coloring or playing music) benefit children? How might this study’s potential results influence professionals working with children?

Question 3 (Understanding method): After children completed the Alternative Uses Task, the originality of their responses was ranked on a scale of 1 (not creative at all) to 5 (highly creative) by a pair of raters. Why would it be important to have multiple raters scoring this task? What issues could potentially arise from this ranking system?

Question 4 (Understanding results): Children who were above average on typical fluency had significant differences between the creative conditions (the free-coloring condition, the book condition, and the color cards condition). These children seemed to perform better in the free-color condition. How would you explain the meaning of this result in your own words?

Question 5 (Implications for life): Although this study did not find a strong connection between EF and creative activity for this sample, it does indicate that individual differences may have an impact on this relationship. How could psychological professionals implement results from this study into their practices?

Emotion and Motivation

Title: Mask-Wearing and Emotional Intensity Perceptions

Authors: Brienna Dove and Teddi S. Deka

Volume: 28

Issue: 1

Page Numbers: 38–45

Direct Link: https://doi.org/10.24839/2325-7342.JN28.1.38

Abstract (Revised): The widespread use of sanitary face masks due to the COVID-19 pandemic renewed interest in facial emotion perception while wearing masks. The use of face masks during this time was considered a nonpharmaceutical intervention to reduce the spread of the virus. The researchers examined whether wearing face masks affects the intensity of emotion perception and judgments of approachability while also considering the sex and age of the rater. Emerging adults (ages 18–25) and adults (ages 26–65) viewed photos of the faces of a young adult man, a middle-aged man, a young adult woman, and a middle-aged woman, masked and unmasked, with happy, sad, neutral, and angry expressions. Tests repeated on the face mask and no face mask conditions showed significant reductions in emotion intensity for happy and sad faces, no differences for angry faces, and the opposite (increased intensity) with neutral faces. Unmasked happy faces were rated as more approachable than masked happy faces. Unmasked angry faces were rated as less approachable than masked angry faces but only by emerging adults. No differences appeared for sad emotions. Neutral faces again showed an unexpected pattern, with masks increasing approachability.

Key Terms:

Emotion Perception: The way one recognizes and makes sense of emotional expressions in others that commonly occurs through facial expressions.

Approachability: The degree to which someone is willing to interact socially with another person, which can be guided by facial expressions and emotional cues.

Emerging Adults: Individuals between the ages of 18–25 years old, considered to be in between the stages of adolescence and adulthood.

Question 1 (Understanding background):

Facial expressions and emotional recognition are fundamentally important regulators of social interactions. Do you feel that widespread mask-wearing during the COVID-19 pandemic affected your social interactions due to a lack of facial “cues?” What were your personal experiences?

Question 2 (Understanding purpose):

Although facial masks may cause misjudgment of facial expressions, they may also increase approachability due to the protection they provide from COVID-19. Would you assume that face masks would generally increase or decrease one’s sociability? In other words, which would you predict has a stronger impact: the deterring effect of masks, or the agreeable effect?

Question 3 (Understanding method):

Participants viewed masked and unmasked faces, and rated their expressions using 9-point scales on the dimensions of happy-sad, calmangry, and approach-avoid. Why was the word “calm” intentionally used instead of “neutral?” Why would word choice be significant in this study?

Question 4 (Understanding results):

There were no significant differences in measures of anger between masked and unmasked “angry” faces. This result was supportive of the hypothesis. Why would anger, specifically, remain consistently rated among masked and unmasked faces?

Question 5 (Implications for life):

This study’s results generally indicate that a masked face may be perceived as happier or more approachable. However, this study was conducted on an 83% White sample at a mid-size, midwestern American university. How might these results change if this study was conducted in an area valuing collectivist ideals?

Personality

Title: Interpersonal Identity Cues: The Effect of Therapist Identity on Expectations for the Therapeutic Relationship

Authors: Jessica S. Philip and Melanie R. Maimon

Volume: 28

Issue: 1

Page Numbers: 67–78

Direct Link: https://doi.org/10.24839/2325-7342.JN28.1.67

Abstract (Revised): Identity cues can impact levels of comfort for marginalized individuals in various contexts, including STEM fields and medical spaces. In this study, the researchers examined whether a therapist’s personality and race can serve as identity cues for racial/ ethnic minority clients and affect the therapeutic relationship. They recruited Asian American and Hispanic/Latinx women (N = 260) for a 3 (trait: high agreeableness, low agreeableness, control) x 2 (race: Black, White) between-subjects experimental study to test the effects of a therapist’s race and personality traits on women’s expectations for a therapeutic relationship and anticipated prejudice from the therapist. They found that racial/ethnic minority women anticipated a more genuine relationship with a Black female therapist and perceived her to be more culturally competent, and less likely to be racist, than a White female therapist. They found no significant differences in perceived prejudice based on the therapist’s personality. Similarly, there were no significant differences in expectations for the therapeutic relationship based on the therapist's personality.

Key Terms:

Identity Threat Cues: An indication that those who are marginalized within a group are likely to be treated unfairly in a social environment.

Identity Safety Cues: An indication that those who are marginalized within a group will experience fair treatment in a social environment.

Prejudice: When someone has negative feelings toward another person or group without having any experience with that person or group.

Cultural Competence: The ability to engage productively with individuals from varying cultural backgrounds in personal as well as professional environments.

Question 1 (Understanding background):

There are prevalent barriers that racial and ethnic minorities experience regarding access to mental health care, which include misdiagnoses and overall dissatisfaction with treatment. Based on the study, in what ways does the concept of identity safety cues relate to these disparities?

Question 2 (Understanding purpose):

The purpose of this study was to find out how Asian American and Hispanic/Latinx women perceive therapeutic relationships based on a therapist’s race and personality. For what reasons might it be important to explore these factors, specifically within the context of disparities regarding mental health?

Question 3 (Understanding method):

Participants were shown varying profiles of therapists that include race (Black or White) and personality traits (agreeable, disagreeable, or control). Given these certain variables, why might researchers choose a between-subjects design? In other words, in what ways does this method aid in isolating the effects of race and personality on participants’ perceptions without the influence of other variables?

Question 4 (Understanding results):

This study’s results showed that participants anticipated having a more authentic therapeutic relationship with Black therapists, which included experiencing a greater level of cultural competence. Where might these perceptions come from and how do they relate to the idea of identity safety cues described in the article?

Question 5 (Implications for life):

This study’s results indicate that representation and perceived cultural competence are essential for fostering a healthy environment within a therapy setting.

Social Psychology

Title: Reducing Ableism and the Social Exclusion of People with Disabilities: Positive Impacts of Openness and Education

Authors: Kaci T. Conley and Dustin R. Nadler

Volume: 27

Issue: 1

Page Numbers: 21–32

Direct Link: https://www.psichi.org/resource/resmgr/journal_2022/27_1_Conley.pdf

Abstract (Revised): Research has shown that people with disabilities (PWD) face ableism, which is associated with their social exclusion. Based on the existing literature regarding the social exclusion of PWD, the researchers hypothesized that higher education levels, personal experiences with PWD, and openness would reduce ableism and negative attitudes toward PWD and increase the social inclusion of PWD. Additionally, they hypothesized that a negative correlation would exist between social inclusion of PWD and ableism and negative attitudes of PWD, moderated by the personality trait openness. Participants consisted of adults (N = 364) who identified as mostly White, female, and nondisabled, and were asked to complete an electronic survey consisting of 4 pre-existing scales measuring ableism, negative attitudes of PWD, social inclusion, and openness. The results showed that higher education levels and personal experiences with PWD predicted lower ableism. Additionally, more openness predicted more social inclusion, less ableism, and higher completed levels of education. Further, voting for conservative political party candidates predicted higher levels of ableism, and voting for liberal political party candidates predicted lower levels of ableism. Although this study had some limitations, it highlights the importance of education and openness in reducing ableism and increasing the social inclusion of PWD.

Key Terms:

Ableism: Discrimination on the basis of favoring those without a disability and explicitly against those with a disability.

Social Exclusion: When people without disabilities do not allow people with disabilities to participate in activities and social interactions on a daily basis.

Openness: Considered a dimension of the Big Five personality model, representing the degree to which a person is open to new experiences involving aesthetic, cultural, or intellectual participation.

Question 1 (Understanding background):

Given the description given in the article about the concept of ableism, in what ways does this system of discrimination and social prejudice affect the opportunities that citizens with disabilities in the United States have, socially and professionally?

Question 2 (Understanding purpose):

In what ways did Conley and Nadler’s research bridge the gap in the existing literature regarding ableism and social inclusion?

Question 3 (Understanding method):

To measure ableism, openness, and social inclusion, what methods did the researchers utilize, and for what reasons were these specific methods chosen for the study?

Question 4 (Understanding results):

In regards to the relationship between openness, education, and ableism, what were the primary takeaways, and in what ways did political orientation play a role in these results?

Question 5 (Implications for life):

In what aspects could the results of this study, regarding ableism and social inclusion, be incorporated in the workplace and various educational settings?

Industrial-Organizational Psychology

Title: Supervisor’s Gratitude and Employee’s Feelings About their Supervisor and Organization

Authors: Emma J. McKeon, Kayla M. Trumbull, and Jennifer L. Hughes

Volume: 25

Issue: 3

Page Numbers: 272–277

Direct Link: https://www.psichi.org/resource/resmgr/journal_2020/25_3_mckeon.pdf

Abstract (Revised): A 2012 survey by the John Templeton Foundation found that a majority of employees said they would feel better about themselves and that they would work harder for a supervisor who was more grateful. These findings prompted the present study which investigated whether employees’ perceptions of their supervisors’ expressed gratitude were predictors of employees’ perceived organizational support, perceived supervisor support, affective organizational commitment, and job satisfaction. They used MTurk to recruit participants and they took online surveys. Using data from 278 respondents, they found that the perception of gratitude expressed by a direct supervisor positively predicted perceived organizational support, perceived supervisor support, affective organizational commitment, and job satisfaction. These results imply that supervisors who express gratitude could increase employees’ positive feelings about their workplace and supervisors.

Key Terms:

Job Satisfaction: How a worker feels about their job, specifically regarding the work itself, the rewards, or the context.

Perceived Organizational Support: How much an organization is perceived as valuing the contributions of the employees and their overall well-being.

Perceived Supervisor Support: How much a direct supervisor is perceived to value the contributions of the employees and their overall wellbeing.

Affective Organizational Commitment: The emotional comfortability that an employee experiences with the organization they work for.

Question 1 (Understanding background):

How might gratitude play a role in the workplace? How does employee-generated gratitude differ from perceived supervisor gratitude?

Question 2 (Understanding purpose):

Why might increasing expressed supervisor support be a beneficial component of the workplace, specifically regarding employees?

Question 3 (Understanding method):

Why was it beneficial to exclude data from 22 participants who gave the same answers throughout the survey? How did the researchers reach that conclusion?

Question 4 (Understanding results):

Findings showed that increasing expressed supervisor support could be a good approach to increase employee-felt support, satisfaction, and commitment. Did these results support the researchers’ hypothesis?

Question 5 (Implications for life): What implications do these findings have for the workplace in terms of increasing employee well-being?

Stress, Lifestyle, and Health

Title: Well-Being and the Outdoors: An Environmentalism Study Among a Religious Student Population

Authors: Laura Pires-Gifford, Shaylee Hoffmann, Edmond Arroyo, Nathan Jones, Bethany Waite, and Robert R. Wright

Volume: 27

Issue: 3

Page Numbers: 185–196

Direct Link: https://www.psichi.org/resource/resmgr/journal_2022/27_3_Pires-Gifford.pdf

Abstract (Revised): Environmental attitudes (EAs, i.e., overall responsibility or general attitudes toward the environment), environmental behaviors (EBs, i.e., willingness to engage in or change behaviors relating to the environment), and environmental concerns (ECs, i.e., concern about environmental issues) are important variables related to outdoor recreation, health behaviors, mental health, and even religion. The present study aimed to examine the relationship between these variables using an online survey of introductory-level students attending a religious university consisting primarily of members of The Church of Jesus Christ of Latter-Day Saints. Results indicate a significant positive correlation between EAs with diet quality (i.e., whole grains, vegetables, and fruits) and life satisfaction, and a negative correlation between EAs and negative affect. EBs were correlated positively with having a high-quality diet, exercise behaviors, life satisfaction, and low levels of negative affect. Interestingly, ECs were correlated with high levels of anxiety, depressive symptoms, perceived stress, diet quality, and low levels of life satisfaction. Although EAs and EBs tended to correlate mostly with positive outcomes, ECs had several negative results implicating differences between EAs, EBs, and ECs. Thus, religious students were more willing and likely to engage in pro-EBs than previous studies have suggested.

Key Terms:

Negative Affect: When someone experiences undesirable emotions involving distress, anger, and or other unpleasant feelings.

Anxiety: Symptoms of anxiety, including feelings of fear and nervousness.

Depressive Symptoms: Symptoms of depression that include feelings of sadness, hopelessness, or a lack of interest in activities that are commonly associated with changes in sleep patterns, appetite, and energy levels.

Stress: When someone experiences the inability to manage the demands of life and often feels overwhelmed.

Life Satisfaction: The extent to which someone perceives life as plentiful, rich, or of high quality.

Question 1 (Understanding background): What do the authors mean when they explain an individual’s view of the environment as a pyramid? How does this understanding relate to environmental attitudes and behaviors?

Question 2 (Understanding purpose): Why would it be relevant to discover the relationship between religion and environmental attitudes, behaviors, and concerns? Why was the Church of Jesus Christ of Latter-Day Saints the religion chosen for this study?

Question 3 (Understanding method): How does a sample consisting primarily of White female participants affect the validity of the study?

Question 4 (Understanding results): Results suggest that religious students are more likely to engage in pro-environmental behaviors, which is not consistent with the findings of other studies. Based on the results of this study, what might explain the differences in findings?

Question 5 (Implications for life): By knowing the factors that influence environmentalism, how can action be directed towards incorporating pro-environmental behavior changes? How might these actions affect environmental stewardship within groups and communities?

Psychological Disorders

Title: Dark Tetrad and Empathy: The Interrelationship of Narcissism, Psychopathy, Machiavellianism, and Sadism with Affective and Cognitive Empathy

Authors: Gayle T. Dow and Hannah Crawley

Volume: 28

Issue: 3

Page Numbers: 229–236

Direct Link: https://doi.org/10.24839/2325-7342.JN28.3.229

Abstract (Revised): The Dark Triad, coined by Paulhus and Williams in 2002, consists of nonclinical psychopathy (violent tendencies and a lack of remorse), narcissism (entitlement and need for admiration), and Machiavellianism (ruthlessness and exploitation); others expanded it to include a fourth construct of sadism (pleasure in other’s suffering). Although the common unpinning of the Dark Tetrad is a lack of empathy, little empirical research has investigated the interrelationship among the components of the Dark Tetrad once empathy is broken down into affective (feeling another’s emotions) and cognitive (understanding another’s emotions) aspects. The purpose of this study was to determine the interrelationship between the Dark Tetrad and affective and cognitive empathy. Over 250 participants completed measures used to assess these constructs. The researchers hypothesized that the Dark Tetrad would be inversely related to affective empathy, but Machiavellianism and narcissism would be positively related to cognitive empathy. The hypotheses were partially supported. Psychopathy, narcissism, and Machiavellianism were significant negative predictors of affective empathy. Psychopathy was a negative predictor whereas narcissism was a positive predictor of cognitive empathy. Theoretical explanations to account for both negative and positive associations of the Dark Tetrad include empathic inducement or the ability to manipulate others by overwhelming them with emotions to solicit a sympathetic response. Future research should seek to examine the differing relationships among these traits, specifically narcissism as it manifests both negative and positive attributes of empathy simultaneously.

Key Terms:

Empathy: Being able to understand a person from their perspective instead of one’s own, through the experience of that person’s feelings, perceptions, and thoughts.

Question 1 (Understanding background): What traits characterize the Dark Tetrad? How do these traits relate to both affective and cognitive empathy, if at all?

Question 2 (Understanding purpose): What does the study help clarify regarding the relationship between the Dark Tetrad and affective and cognitive empathy?

Question 3 (Understanding method): What factors help explain the low internal reliability of the study? What makes empathy difficult to measure, and what choices were made to most accurately assess empathy for this study?

Question 4 (Understanding results): What trait of the Dark Tetrad did not appear to have a relationship with both affective and cognitive empathy? What might explain this? Do these results mirror or oppose the results presented in previous studies?

Question 5 (Implications for life): How might these findings impact interpersonal relationships? Could malevolent activity be prevented with the knowledge gained from the results of this study?

Therapy and Treatment

Title: The Effects of App-Delivered Cognitive Behavioral Therapy for Insomnia (CBT-I) on Sleep Quality, Dysfunctional Beliefs, and Sleep Hygiene

Authors: Julia A. Leonard and Angela B. Duncan

Volume: 25

Issue: 3

Page Numbers: 224–233

Direct Link: https://www.psichi.org/resource/resmgr/journal_2020/25_3_leonard.pdf

Abstract (Revised): Sleep quality is correlated with physical and mental health and is an important target for overall well-being. Cognitive Behavioral Therapy for Insomnia (CBT-I) is an evidence-based strategy to improve sleep quality; however, a shortage of qualified providers, logistical issues such as cost, travel, and time, privacy concerns, and a desire to resolve symptoms on one’s own limit access to CBT-I. Compared to traditional face-to-face or web-based delivery of CBT-I, app-delivered CBT-I may be an efficacious alternative capitalizing on the portability, privacy, and accessibility of mobile phones. The present study examined the effectiveness of the CBT-I Coach in educating participants about the importance of healthy sleep practices and dysfunctional beliefs about sleep and targeted sleep. The use of the CBT-I Coach resulted in significant improvements in sleep quality, dysfunctional beliefs about sleep, sleep hygiene behaviors, and sleep efficiency. This study supports the use of CBT-I Coach as an effective intervention for improving sleep quality.

Key Terms:

Sleep hygiene: A combination of healthy sleep habits and optimal environmental factors that foster a good night’s sleep.

Sleep efficiency: The ratio of the total amount of sleep received to the total amount of time in bed, thus measuring insomnia.

Question 1 (Understanding background): How might poor sleep quality affect mental and physical health? What role does cognitive behavioral therapy for insomnia (CBT-I) play concerning sleep quality?

Question 2 (Understanding purpose): What factors limit access to traditional CBT-I? How might internet-based interventions, like the CBT-I Coach app, benefit individuals with dysfunctional beliefs about sleep or who struggle with sleep difficulties? What are the limitations of internet-based interventions?

Question 3 (Understanding method): Why would researchers desire participants who were not involved in treatment for sleep difficulties at the time of the study? Why would researchers have participants partake in multiple baseline measures before and after participating in the study?

Question 4 (Understanding results): Results from this study indicate that app-delivered CBT-I significantly improved sleep quality and decreased dysfunctional beliefs about sleep and problematic sleep behaviors. Did these results support the researchers’ hypotheses?

Question 5 (Implications for life): How might the incorporation of internet-based interventions, like the CBT-I Coach app, be relevant in our world today? Based on the results of this study, could these internet-based interventions have the possibility to treat other problematic behaviors unrelated to sleep?

EINVITED EDITORIAL:

Involving Undergraduate Students in Programmatic Research: Social

Media Use Among Brigham Young University–Idaho Students

(Part of the 2024/25 Editorial Series: Collaborating With Students in High-Quality Publishable Research)

Robert R. Wright Department of Psychology, Brigham

Young University–Idaho

ngaging students in research has always been a passion of mine. I love interactional learning that occurs as a professional works alongside a pupil, demonstrating through experiential learning the way to do a difficult task. Certainly, research is a difficult task. In this editorial, consistent with other recommendations I have made previously (Wright et al., 2022), I describe a programmatic line of research I have conducted with many undergraduate students at Brigham Young University–Idaho (BYU­Idaho) over the years on a topic that many students find fascinating both professionally and personally: social media use and its ties to health and well­being.

For as long as I can remember, I have always enjoyed university and college campuses, taking time to walk around and explore them. As I have done so over the years, however, I have noticed a change in the greetings I received, as most students were so immersed in some technologically induced distraction that I hardly receive a head nod sometimes. This observation combined with the discouraging statistic that as many as 80% of undergraduate students will experience loneliness at some point in their academic career (Zhao et al., 2012) and the recent declaration that loneliness is an epidemic (U.S. Surgeon General., 2023) led me to examine the sociotechnological context of college students. Many would agree that campus culture is unique, and some have even remarked that college students are having “the time of their lives” (Coccia & Darling, 2016). However, the influence of this pervasive use of technology may be coming at a cost to their health and wellness. So, I set out to investigate, and I enlisted several students along the way, as my “subject matter experts.”

Social Media and Health

First, using a snowball sampling technique, I gathered data along with several student research assistants (Kolby Hardy, Sydney Shuai, Madison Egli, and Rhett Mullins) and we published our findings in the Journal

of Technology in Behavioral Science (Wright et al., 2018). With this methodology, my research students actively recruited students in existing classes and they, in turn, recruited other students to participate by completing an online survey questionnaire. Accordingly, we amassed many participants (n = 579) in a relatively short time. Participants (M age = 22.22; White = 85%; single = 68%) provided responses regarding their own perceived loneliness, daily time spent on social media, and several health behaviors and outcomes. Results highlighted some important relationships starting with loneliness, which was strongly related to depressive symptoms (r = .58) and modestly related to many health behaviors and outcomes. Next, we examined how relationship status interacted with loneliness and, sure enough, both men and women decreased significantly in their reports of loneliness when engaged and married compared to those who were single. Then, we explored social media use, and although daily social media use was not related to as many variables as loneliness, we discovered that, as daily time on social media increased, so did reports of both loneliness (r = .21) and depressive symptoms (r = .20), suggesting that a modest relationship existed. Finally, we discovered that women consistently reported higher levels of loneliness and daily social media time than men. However, importantly, we found that men and women had similar trajectories of loneliness as social media time increased, regardless of relationship status. In other words, those who spent more daily time on social media had worse associated health profiles, regardless of gender or relationship status. Although causation cannot be determined, there are a few potential conclusions that could be drawn. First, since women consistently reported higher perceived loneliness than men across all analyses, it may be that women are more aware of their social context than men (and hence, more accurate), more honest than men in their self­reports, or it could be that women do, in fact, actually experience more loneliness and spend

more time on social media than men. In the literature, there is support for all three explanations (Nowland et al., 2018). Second, even as women’s social media time was consistently higher than men, it may be that women students are more prone to seek out online social connections. Third, spending more time on social media corresponds with increases in loneliness perceptions, suggesting that prevention of loneliness may be facilitated by spending less time on social media platforms. This suggests that people may be drawn to social media as a form of social connection, but discover that virtual interactions provide unfulfilled expectations, perceived deficits in social comparisons, or other detrimental cognitions and emotions.

Indeed, it seems that social media may offer a more attractive forum for human interaction upfront to our students, especially for women, but in the end, it is less fulfilling compared to face ­ to ­ face interpersonal interactions, being associated with greater psychosocial distress. In fact, Kolby Hardy, one of my student research assistants, likened social media as the “empty calorie of communication” when interviewed by a regional newspaper (Weaver, 2017). My student research assistants were incredibly interested in these findings and loved the process of collecting and analyzing the data, and then writing up a report for publication on a topic very applicable and integral to their lives. Plus, they were able to provide a critically important perspective that helped us interpret these findings in the context of student life.

Shortly after the publication of these findings, I was unexpectedly contacted by Joya Inc., the company behind the popular app, Marco Polo. Upon reading our findings (Wright et al., 2018), they wanted to test whether users of Marco Polo would report lower levels of loneliness than users of other popular apps. I was intrigued, so I agreed to conduct two studies: one among our students (Wright et al., 2020) and another among a larger, more diverse sample across the contiguous Western U.S. (Wright et al., 2021). Both of which, I should point out, were published in the Psi Chi Journal of Psychological Research . Again, I invited several student research assistants to join me (Rhett Mullins, Chad Schaeffer, and Austin Evans). Despite not being as familiar with the original study, these student researchers were able to get on board rather quickly and presented our findings at a regional convention (see Figure 1).

First, we recruited students to complete an online survey questionnaire that queried time spent on specific social media apps along with a host of psychosocial health variables (e.g., anxiety, depressive symptoms, loneliness). Participants (n = 630) demonstrated what we had observed before: increased daily time spent on any

social media was related to higher loneliness, negative mood, depressive symptoms, anxiety as well as lower life satisfaction. However, when considering specific social media platform (i.e., Facebook, Instagram, Snapchat, LinkedIn, Marco Polo, WhatsApp), we noticed some differences. Comparing those who had the app (users) to those who did not (nonusers), we noticed that those who used Snapchat had the worst associated health profile (compared to Snapchat nonusers) with higher depressive symptoms, loneliness, negative affect and lower satisfaction with life. Facebook users reported similar higher loneliness and lower subjective overall health. However, Marco Polo users demonstrated an opposing picture; users showed higher positive affect and lower loneliness than nonusers. Instagram and LinkedIn student users had some similar positive profiles as Marco Polo users, though not as strong. In our second study among adults across the Western U.S. ( n = 2,023), we found very similar results (Wright et al., 2021), which engendered additional confidence in our student sample findings. As such, it seems that, while increased time on social media is associated with problematic health profiles, the specific social media platform may make a difference. Although I could have done these studies on my own, I must mention that having motivated and capable student researchers helped save me time and provided essential assistance in practical study design and interpretation of the results. For instance, up to that point, I had never heard of Marco Polo or WhatsApp before!

Social Media: New Platforms and Motives for Use

In this field of studying human interface with technology, findings quickly become antiquated. Indeed, some enterprising students (Chris Nienstedt, Nathan Smith, Hannah Braithwaite, and Ben Gilbert) proposed two study ideas that helped address some gaps, again highlighting the integral role my student research assistants took in this programmatic research. First, we devised a follow­up study focused solely on TikTok users versus nonusers (Nienstedt et al., 2023) by administering an online questionnaire to a sample of students (n = 407) using a similar research protocol and statistical procedure as done previously. TikTok users reported poorer psychosocial well­being than their nonuser counterparts in almost every domain (i.e., negative mood, perceived stress, body image, anxiety, depressive symptoms, self­regulation), but when controlling for gender, we discovered that these relationships were only present among women. Thus, TikTok users, especially women, seemed to fare worse in terms of psychosocial health and well­being than those who did not use TikTok, suggesting (again) that women students may be particularly susceptible or vulnerable to platforms like TikTok.

The second study (done with Carson Ewing, Chris Nienstedt, and Samuel Chambers) was born out of the concern that people turn to social media for different reasons. Indeed, there are a host of potential motivations for using social media and many of these could inherently be good, such as wanting to keep in touch with distant others. Fortunately, we had been gathering data for many semesters (spring 2020 to spring 2022) from our students and had a large sample (n = 1,547) for this study (Ewing et al., 2023). Through correlational analysis, our findings highlighted unique differences in social media motives and how they are related to user demographic characteristics, electronic media use, and health indicators. The motive of entertainment stood out above all the others. Those who scored higher on entertainment had increased troubling electronic media use variables (i.e., addictive smartphone behavior, daily social media time, television watching time) as well as greater problems with sedentary behavior, depressive symptoms, negative mood, poor body image, anxiety, loneliness, and physical symptoms. Follow­up analyses further revealed that first­ and second­year students had higher entertainment ratings, and those who were married had the lowest ratings. Thus, students who use social media for entertainment purposes reported poorer health and wellness, with first­year students and sophomores at greater risk and married students at lower risk. Not only did we uncover interesting results, but my student researchers were thrilled to share them with others at a professional psychological convention (see Figure 2) and publish their findings as undergraduate student first authors, providing foundational experiences for them as many departed for doctoral graduate programs thereafter.

Dating Apps Use

My studies up to this point had neglected to consider another major arena for social media use among students: the dating scene. In fact, a group of students (Lindsay Johnson, Brandon Jones, Maren Batman, Lavear Whitney, Kiyomi Miyasaki, and Anna Aho) in my advanced research course approached me with another intriguing proposition: to examine dating apps use and associated student health. Through an online questionnaire to General Psychology students, participants (n = 818) reported on their psychological, emotional, and psychosocial well­being and whether they used dating apps for their own dating. Comparing those who used dating apps (23.7%) to those who did not, we uncovered several differences such that those who were using dating apps reported fewer dates, lower quality of dating experiences, and that dating was a higher priority for them than those who were not using

dating apps (Johnson et al., 2025). Moreover, dating apps users reported lower body appreciation, satisfaction with life, and social support as well as greater loneliness and depressive symptoms than nonusers.

These results were not surprising to us in the campus context of BYU­Idaho, as many who are not pleased with the dating context or even with themselves may resort to alternative dating means. However, the next set of analyses were not what we expected. Specifically, those who used dating apps were reporting lower levels of met psychological needs (i.e., autonomy, competence, relatedness; Ryan & Deci, 2002) and generally poorer levels of emotional experience (e.g., increased negative mood, greater diversity of emotion). Although the methodology behind these results precludes causal conclusions, these findings suggest that those who are dissatisfied with their social environment (dating) or are trying to compensate for social skills deficits are more likely to turn to dating apps for technology­mediated assistance. Thus, using dating apps may not cause poorer psychological, emotional, and social well­being per se, but may attract a particular group within the population. What is interesting to note, however, is that to best investigate some of these types of contemporary issues, having student research assistants may not only be nice, but essential. Some of the best original research ideas I have encountered have originated from students who may be more in­tune with contemporary phenomena, or can provide a fresh perspective.

COVID-19 and Freshmen Students

Amid ongoing data collection in my lab, a major historical event occurred known as the COVID­19 pandemic. We found ourselves with a researcher’s dream: the ability to investigate possible impacts of the pandemic. The focus of our study (done with Jordan Larson, Sarah Richards, Shaylee Larson, and Chris Nienstedt) was to examine the relationship of technology use (i.e., television, social media, computer/tablet, screen time) with health and wellness variables and compare these associations both before and after the pandemic. We could not establish a causal effect, since we did not look at the same participants over time but between the two cohorts (Wright et al., 2023). Nevertheless, between our students in the prepandemic cohort (n = 367) and pandemic cohort (n = 598; after March 2020), we noted several differences. First, there was a substantial increase in daily spent time on television, social media, and screens. In fact, total screen time increased by more than 3 hours per day! Whether you believe screen time is healthy or not, we can all agree that 3+ hours per day increase in any activity will have an impact on one’s health. Second, body mass index, physical health complaints, and sugary

drink consumption increased and, paradoxically, fruit and vegetable consumption as well as sleep quality improved, suggesting that the pandemic restrictions were associated with some mixed differences. Third, social interaction dramatically decreased by more than 50%, suggesting that the restrictions were effective at limiting social interaction. Finally, the irony of this next point is not lost on me: all my student research assistants collaborated with me via electronic means throughout this project. It was imperative again that I had student research assistants to not only provide help with data collection and literature review (the more traditional tasks), but also to elucidate our findings through experience and content familiarity.

Building on the implications of these findings, we conducted another study on one subset of the student population that might have been the most impacted by the pandemic social restrictions, namely newly incoming first semester students. First semester students are more susceptible and vulnerable to many environmental conditions, particularly because their lives are undergoing upheaval, both academically and socially. During this same time period, we conducted another study that focused on first semester freshmen (FSF). This time we examined three cohorts: pre­COVID, during COVID (March 2020 to August 2021), and post­COVID (Wright et al., 2025). We examined health and wellness along with similar technology use variables as our previous study with 2,500 student participants from General Psychology courses completing an online survey questionnaire between the years of 2018–2023. Although I did not have any first semester students on my research team for this project, again, having student researchers assist in this project proved vital.

In fact, I had some very interested, invested student researchers (Skyler Brough, Joshua Castro, McKenna Osborne, Lindsay Johnson, and Spencer Johnson) so that I could turn over several semesters’ worth of data to them for exploration and analysis. Our analyses uncovered very interesting results. First, FSF health and demographic metrics varied little across the three cohorts, suggesting a return to prepandemic levels. However, FSF indicated an higher subjective physical health at Post, but, paradoxically, also higher physical health complaints. We believe this is a function of a shift in comparison metrics, as the pandemic has heightened personal awareness of physical symptoms while simultaneously demonstrating that others’ symptoms (likely with COVID­19) are worse. One other finding highlighted that social integration decreased while daily screen time increased, suggesting that our FSF might have been using technology to compensate for the decreased social contact.

Figure 1

Research Group at the Rocky Mountain Psychological Association Convention, Denver, CO 2019

Figure 3

Award Winners at the Rocky Mountain Psychological Association Convention, Denver, CO 2024

Figure 2

Research Group at the Rocky Mountain Psychological Association Convention, Albuquerque, NM 2023

Second, comparatively, FSF reported being in poorer health and well­being compared to their respective non­FSF counterparts across all three cohorts. This included higher loneliness, social media, physical symptoms, anxiety, and depressive symptoms as well as poorer sleep quality. The sole variable where FSF health was higher was social integration, especially post­COVID. Thus, it seems the COVID­19 pandemic might have impacted FSF more strongly than others, suggesting this is a population vulnerable to dramatic social changes that might have implications for college enrollment and retention. After discovering these differences, my pioneering student research assistants took this project to a regional convention, were awarded the student research award (see Figure 3), and published in the Psi Chi Journal of Psychological Research, furthering their own career aspirations. Having student researchers assist on this project allowed exploration of large amounts of data, allowed them to offer new insights, and provided them, a very motivated group of students, the complete research experience up to publication.

Conclusion

Although the demands of research, especially programmatic research (e.g., time, training), may dissuade some from having undergraduate student research assistants, I have offered my experience as a case study example of how this can be done. My hope in writing this has been to shed light not only on the how, but that perhaps, in many cases, the why. I am still amazed at the number of good research ideas generated by my students that turned into publishable projects, even as one student idea built on another. The benefits of gaining research experience for undergraduate students is certainly notable, but a faculty researcher can still benefit greatly by incorporating undergraduate students in the process including saving precious resources (i.e., time, money) while providing assistance in research progression. By maintaining flexibility along with appropriate guidance and scaffolding by an experienced researcher, quality programmatic research can be conducted and enriched with undergraduate student researchers. In this light, I would encourage all to consider the potential benefits of having student research assistants, particularly within a programmatic line of research on practically important topics of contemporary interest to society and students themselves.

References

Coccia, C., & Darling, C. A. (2016). Having the time of their life: College student stress, dating and satisfaction with life. Stress and Health, 32(1), 28–35. https://doi.org/10.1002/smi.2575

Ewing, C. R., Nienstedt, C., Wright, R. R., & Chambers, S. (2023). Social media use motives: An influential factor in user behavior and user health profiles. Psi Chi Journal of Psychological Research, 28(4), 375–286. https://doi.org/10.24839/2325-7342.JN28.4.275

Johnson, L., Wright, R. R., Jones, B. A., Batman, M., Whitney, L., Miyasaki, K., & Goodman, A. (2025). Dating apps users among emerging adults: A profile of emotional and psychosocial well-being. Psi Chi Journal of Psychological Research, 30(1), 51–64. https://doi.org/10.24839/2325-7342.JN30.1.51

Nienstedt, C., Smith, N., Braithwaite, H., Gilbert, B., & Wright, R. R. (2023). Swiping away our well-being? Examining TikTok use among college students. Psi Chi Journal of Psychological Research, 28(2), 96–106. https://doi.org/10.24839/2325-7342.JN28.2.96

Nowland, R., Necka, E. A., & Cacioppo, J. T. (2018). Loneliness and social internet use: Pathways to reconnection in a digital world? Perspectives on Psychological Science, 13, 70–87. https://doi.org/10.1177/1745691617713052

Ryan, R. M., & Deci, E. L. (2002). Overview of self-determination theory: An organismic dialectical perspective. In E. L. Deci & R. M. Ryan (Eds), Handbook of self-determination research, 2, 3–33. University of Rochester Press.

U.S. Surgeon General. (2023). Our epidemic of loneliness and isolation: The U.S. Surgeon General’s advisory on the healing effects of social connection and community https://www.hhs.gov/sites/default/files/surgeon-general-socialconnection-advisory.pdf

Weaver, S. J., (2017). BYU-Idaho study links loneliness to social media use Deseret News, Church News, November 19, 2017.

Wright, R. R., Brough, S., Castro, J., Osborne, M., Johnson, L., & Johnson, S. (2025). State of the first semester freshman: Health and wellness through the COVID-19 pandemic, years 2018-2023. Psi Chi Journal of Psychological Research, 30(1), 65-83. https://doi.org/10.24839/2325-7342.JN30.1.65

Wright, R. R., Evans, A., Schaeffer, C., Mullins, R., & Cast, L. (2021). Social networking site use: Implications for health and wellness. Psi Chi Journal of Psychological Research, 26(2), 165–175 https://doi.org/10.24839/2325-7342.JN26.2.165

Wright, R. R., Hardy, K., Simpson, S., Egli, M., Mullins, R., & Martin, S. (2018). Loneliness and social media use among religious Latter-day Saint college students: An exploratory study. Journal of Technology in Behavioral Science, 3(1), 12–25. https://doi.org/10.1007/s41347-017-0033-3

Wright, R. R., Larson, J., Richards, S., Hoffmann, S., & Nienstedt, C. (2023). The COVID-19 pandemic: Electronic media use and health among U.S. college students. Journal of American College Health, 72(9), 3261–3276 https://doi.org/10.1080/07448481.2022.2155463

Wright, R. R., Schaeffer, C., Mullins, R., Evans, A., & Cast, L. (2020). Comparison of student health and well-being profiles and social media use. Psi Chi Journal of Psychological Research, 25(1), 14–21. https://dx.doi.org/10.24839/2325-7342.JN25.1.14

Wright, R. R., Treadwell, K. R. H., & Hughes, J. L. (2022). Invited editorial: Sharing effective models of student research mentoring: Stories from associate editors. Psi Chi Journal of Psychological Research, 27(3), 223–228. https://doi.org/10.24839/2325-7342.JN27.3.223

Zhao, J., Kong, F., & Wang, Y. (2012). Self-esteem and humor style as mediators of the effects of shyness on loneliness among Chinese college students. Personality and Individual Differences, 52, 686–690. https://doi.org/10.1016/j.paid.2011.12.024

Author Note

Robert R. Wright https://orcid.org/0000000241017840 Correspondence concerning this article should be addressed to Robert R. Wright, Department of Psychology, Brigham Young University–Idaho, 210 West 4th South, Rexburg, ID 83460­2140. Telephone: 208­496­4085. Email: wrightro@byui.edu

Effects of Controllability and Language on Stigma Toward Mental Illness

Claire E. Shaver, Kevin M. Summers, Gina A. Paganini, and E. Paige Lloyd* Psychology Department, University of Denver

ABSTRACT. Although previous research has consistently found that people tend to stigmatize mental illness, it is important to explore the psychological factors that influence this stigma and the various dimensions of stigma involved (e.g., fear, perceptions of dangerousness, and willingness to offer help; Brohan et al., 2010). In the current study (n = 438), we manipulated the controllability of fictitious mental illnesses (between­subjects; controllable vs. uncontrollable) and examined participants’ stigmatization across 6 dimensions (e.g., fear, help, forcing treatment, and negative emotions; Brown, 2008) but many fail to have documented or adequate psychometric properties. The purpose of this study was to further evaluate the psychometric properties of one such measure, the Attribution Questionnaire. We also examined whether effects of controllability on stigmatization were moderated by language (within­subjects; person­first vs identity­first). In the low (compared to high) controllability condition, participants responded with more fear, empathy, negative emotion, and intention to force treatment, but attributed less responsibility and tendency to help (p < .001). We found no evidence for a main effect of language ( p = .06). Language condition did not moderate effects of controllability on dimension of stigma (p = .38). This study highlights the multifaceted nature of mental health stigma and suggests that controllability may be an important, but nuanced, factor in mental health stigma.

Keywords: person­first language, controllability, mental health stigma, dimensions of stigma

Human societies exhibit group­based hierarchies, leading to the devaluation of individuals based on social identity, appearance, or health—a phenomenon known as stigma (Sidanius et al., 2004; Sidanius & Pratto, 2003). Mental health stigma is one of the most prevalent forms of stigmatization and affects millions of Americans (APA, 2021; Mental Health Foundation, 2021), with significant consequences for their well­being (Angermeyer & Dietrich, 2006; Dietrich et al., 2004; WHO World Mental Health Survey Consortium,

2004). Stigma comprises stereotypes, emotional responses, and behaviors towards marginalized groups (Brohan et al., 2010), reflecting societal attitudes towards certain characteristics or identities (Earnshaw & Karpyn, 2020; Lacey et al., 2015; Lau et al., 2016).

Controllability, or beliefs about a person’s agency over a stigmatized characteristic, is theorized to play a role in mental health stigma (Feldman & Crandall, 2007; Kvaale et al., 2013; Larkings & Brown, 2018). However, its effects can vary depending on the dimension

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Shaver, Summers, Paganini, and Lloyd | Controllability and Language on Stigma

of stigma being studied (Angermeyer et al., 2015). Additionally, language choice in describing mental health conditions has gained attention, with personfirst language theorized to reduce stigma compared to identity­first language (Granello & Gibbs, 2016). Despite some evidence supporting this supposition, findings are inconsistent (Baker et al., 2022). For the current study, we aimed to investigate the main and interactive effects of controllability and language on mental health stigma across various dimensions, contributing to a more comprehensive understanding of mental health stigma, its predictors, and multifaceted structure.

Stigma as a Multidimensional Construct

Previous research has encouraged researchers to explore what factors may play a critical role in how perceivers stigmatize people (see Cariello et al., 2021; Link, 2001; Link & Phelan, 2001). The effects of stigma have been examined for a wide variety of identities and across a wide range of contexts (Angermeyer & Dietrich, 2006), and although scientific definitions of stigma vary, effects on well­being are fairly uniform. However, within this research, stigma has been defined with different constructs, such as perceived dangerousness, anger, unwillingness to help, empathy, and many more (Dietrich et al., 2004), which may explain inconsistent results across studies of what factor increases stigma (e.g., Brohan et al., 2010; Fox et al., 2018; Hayward & Bright, 1997; Herek et al., 2002; Livingston & Boyd, 2010).

In sum, it appears that stigma is not a monolith but a multidimensional construct. Given this past research, the current study similarly operationalized stigma using a multidimensional approach. This allows for us to explore whether any effects we find are moderated by the dimension of stigma being examined—creating complexity and nuance in our findings. Specifically, we examined the influence of each predictor on six dimensions of stigma.

Controllability Beliefs as Stigma Antecedents

Controllability beliefs—or the extent to which one believes a person can work to change or is responsible for the stigmatized characteristic/identity through their own volitional behavior—seem to predict mental illness stigma (Knettel, 2019). One study found that perceived controllability predicted social rejection towards people with mental illness better than 16 other factors (e.g., dangerousness or rarity; Feldman & Crandall, 2007). Other studies found that perceived controllability accounted for 24% of the variance in stigma towards people with mental illnesses (Towler & Schneider, 2005).

Researchers have operationalized controllability by considering etiology. Genetic conditions for mental

illness represent low controllability, whereas behavioral explanations suggest high controllability (Corrigan et al., 2000; Uher, 2014). However, the effects of controllability on stigma vary based on the type of stigma under examination. For instance, biological explanations are associated with less blame but more perceptions of danger and desire for distance (Kvaale et al., 2013). Despite some evidence suggesting that high controllability leads to more stigma, there are conflicting findings (Goldstien & Rosselli, 2003).

To address these inconsistencies, we employed fictitious mental health conditions to minimize variability in beliefs about controllability and utilized a multidimensional measure of stigma. Our predictions aligned with previous research, anticipating greater stigma towards conditions perceived as highly controllable, although we recognized that this effect may depend on dimension of stigma.

Contextual Factors:

Language in Communicating Stigma

In addition to controllability, the current study also manipulated language, specifically person­first versus identity­first. Beliefs about controllability and linguistic choices may be related, despite being distinct constructs. Identity­first language (e.g., “smoker”) implies a lack of agency, suggesting that, in a controllability context, it may lead to less stigma compared to person ­ first language (e.g., “person who smokes”), which implies agency (controllable; Williamson et al., 2020). This aligns with the language preference of some communities. For example, representatives from the autistic and Deaf communities explicitly advocate for identity­first language, stating that it reduces the stigma toward their communities (American Psychological Association, 2021; Kenny et al., 2016).

Conversely, empirical evidence has suggested that identity­first language may reduce individuals to “only” their identity, prompting responses based on perceivers’ stereotypes of the stigmatizing characteristic rather than individualizing the person. For example, some studies found that identity ­ first language (i.e., “mentally ill people” and “schizophrenics”) led to greater stigma than person­first language (i.e., “people with mental illness” and “people with schizophrenia;” Granello & Gibbs, 2016; Granello & Gorby, 2021). Thus, there are reasons to expect that identity­first language could generate more or less stigma relative to person­first language.

However, although several studies have found that language type informs stigma, others have observed nonsignificant effects (Baker et al., 2022; Granello & Gibbs, 2016). These conflicting effects could be attributed to differences in the operationalization of stigma

Controllability and Language on Stigma | Shaver, Summers, Paganini, and Lloyd

(Chang et al., 2016). Within the previously mentioned studies, stigma was captured differently depending on whether the study aimed to capture beliefs, emotional responses, or behavior towards individuals with mental illness. For example, Baker and colleagues (2022) examined stigma through different subscales (i.e., authoritarianism, benevolence, social restriction, and community attitudes) and found contradictory evidence across subscales. In the authoritarianism and social restrictiveness subscales, they found that identity­first (relative to person­first) language yielded greater stigma, whereas in the benevolence and community health ideology subscale, identity­first (relative to person­first) language yielded less stigma.

These findings suggest that the effects of language on stigmatization could differ by the dimension of stigma considered. In this study, we built off these findings by examining the effects of person­first and identity­first language across different dimensions of stigma. Due to the mixed theorizing and empirical evidence regarding the effect of language on stigma, we expected that language could influence stigma and may differ by dimensions of stigma, but we remained agnostic regarding which language­type (person­first vs. identity­first) would yield relatively lower stigma.

Interactive Effects of Language and Controllability on Stigma

As mentioned, language effects may vary based on the mental illness and the stigma dimension examined (Benson et al., 2016; Granello & Gibbs, 2016; Kelly & Westerhoff, 2010). We also proposed that language effects may also depend on controllability of the mental illness. Research on substance use disorders suggests that, if an illness is viewed as controllable, person­first language generally reduces stigma compared to identityfirst language (Ashford et al., 2019; Baker et al., 2022; Goodyear et al., 2018; Kelly et al., 2010). Thus, personfirst language may evoke more positive perceptions of highly controllable conditions (Angeli et al., 2012; Brown, 2012; Ferrigon, 2019; Mitchell & Locke, 2015).

Conversely, some members of the Deaf community have argued that identity­first language is less stigmatizing as it values their disorder as part of their identity (Brown, 2012; Kenny et al., 2016). Deafness, typically seen as low in controllability and genetic in origin, suggests that identity­first language might be preferable when the condition is not perceived as controllable. In sum, language effects might differ based on the controllability of the condition.

Leake and colleagues (2022) tested this hypothesis by having participants read vignettes differing by language type about hypothetical mental illnesses explained

with a genetic attribution (indicating low controllability) or a behavioral attribution (indicating high controllability). They observed a nonsignificant interaction (p = .05) with a small effect size (ηp2 = .03) between language type and perceived controllability on stigma; descriptively, in high controllability conditions, identity­first language led to greater stigma than person­first language, whereas in low controllability conditions, the effects reversed. Notably though, Leake and colleagues employed a single composite measure of stigma (i.e., 5­item modified version of the Self ­ Stigma of Mental Illness Short Form; Corrigan et al., 2012)which harms self­esteem, self­efficacy, and empowerment. Previous research has evaluated a hierarchical model that distinguishes among stereotype awareness, agreement, application to self, and harm to self with the 40­item Self­Stigma of Mental Illness Scale (SSMIS, and their study was underpowered. Aligned with Leake and colleagues (2022), we predicted that highly controllable mental illnesses would be more stigmatized when described with identity­first (compared to person­first) language, whereas disorders perceived as less controllable would be less stigmatized when described with identity­first (compared to personfirst) language. But departing from Leake and colleagues, we explored this question through a multidimensional definition of stigma to enable more complex insights into the interactive influence of language and controllability on stigma.

Overview of Current Work

The current study bridged a gap by considering both predictors in the same study enabling examination of an interactive effect. Importantly, diverging from Leake and colleagues (2022), this study posed a more robust examination of how these predictors influence stigma by examining multiple dimensions of stigma. In this study, we not only expanded the empirical evidence surrounding how controllability (low vs. high) of a mental illness influences stigma, but also contributed to the on­going debate of how language (person­first vs. identity­first) may influence dimensions of stigmatization.

We assessed how people stigmatize hypothetical mental illnesses by manipulating the language used (person­first vs. identity­first) and the level of controllability (low vs. high). Our study used a mixed­model design with language type as a within­subjects factor and controllability as a between­subjects factor. Participants read two vignettes describing a fictitious mental illness—one vignette employed with person­first language and one with identity­first language. Participants were randomly assigned to either read vignettes that communicated high or low controllability. After reading each vignette, participants rated their stigmatization

of the fictitious conditions across six dimensions: fear/ dangerousness, help/interact, responsibility, forcing treatment, empathy, and negative emotions (adapted from Brown, 2008).

We predicted a significant main effect of controllability on stigma, such that high controllability would result in greater stigma than low controllability. We remained agnostic regarding if person­first (compared to identity­first) would lead to less or more stigma. Further, we predicted an interaction between language type and controllability on stigma. Within the high (compared to low) controllability condition, we predicted that participants would exhibit greater stigma toward conditions described with identity­first, compared to person­first, language. Additionally, we also explored how these effects might be moderated by dimensions of stigma. We expected differences across dimensions but did not have specific predictions given the novelty of these questions.

Method

Participants

We aimed to recruit the largest sample possible given available funding. We recruited 438 participants via CloudResearch from MTurk (an online recruitment platform; Litman et al., 2017)Mechanical Turk (MTurk. A sensitivity analysis conducted in G*Power (V3.1; Faul et al., 2007) indicated that 438 participants enabled us to detect a medium (np2 = .07) effect with 80% power in a 2 × 2 mixed model factorial ANOVA. All participants who provided data were included in analyses1

Our sample was predominantly White (79.4% White, 9.9% Black/African American, 4.8% East Asian, 0.2% Native Hawaiian/Pacific Islander, 1.4% South Asian, 2.1%, bi­ or multiracial, 0.7% other, and 1.4% did not disclose). Over half of participants were men (47% men, 45.5% women, 0.9% as nonbinary, 0.2% as agender, 0.2% as other and 0.2% did not disclose; participants could select more than one gender category), and most identified as non­Hispanic/Latinx (82.0% not Hispanic/Latinx, 9.3% Hispanic/Latinx, and 3.0% did not disclose). Participants were between 20–81 years old with the mean age of 39.86 (SDage = 11.67) Participants were compensated $1.00 for their participation in the 10­minute survey.

Materials

Vignettes

We employed vignettes to describe hypothetical mental illnesses and to systematically vary both the language used to describe the conditions (person­first

1 Degrees of freedom or n maybe fluctuate because some participants did not complete all items.

vs. identity­first) and the controllability of the conditions (low vs. high). Participants in the current study viewed two vignettes describing hypothetical mental illnesses named Grespar and Munder. The names of the hypothetical mental illnesses (i.e., Grespar and Munder) were selected based on pretesting from a set of 21 hypothetical condition names (50 participants recruited from CloudResearch; Paganini et al., 2022). Importantly in this pretest, Grespar and Munder did not differ in perceived negativity. Participants were randomly assigned to one level of controllability (i.e., each participant read about two low controllable conditions or two high controllable conditions) and saw one vignette for each language type and condition name (i.e., each participant read about one condition described with identity­first language and the other described with person­first language). Participants were told this was a hypothetical mental illness.

To control for order effects or potential confounds, the viewing order of language was randomized, and condition names paired with controllability were counterbalanced between subjects. We chose to manipulate controllability between­subjects because we were concerned that participants might identify our hypothesis if controllability was manipulated within­subjects; whereas we manipulated language (which we believe is a more subtle manipulation) within­subjects to enhance power2.

To illustrate our manipulations of controllability and language, a sentence from the person­first, low controllability Munder vignette read, “For people with Munder, their symptoms cannot be easily controlled, and their symptoms are often unresponsive to drug or psychotherapies and lifestyle changes (e.g., sleep, diet).”

The same sentence from the identity­first, high controllability Grespar vignette read, “For Grespar people, their symptoms can be easily controlled, and their symptoms are often responsive to drug or psychotherapies and lifestyle changes (e.g., sleep, diet).” The full vignettes for each condition are included in the Appendix.

Controllability Manipulation Check

Controllability is multifaceted, so our manipulation included statements that might have tapped into multiple dimensions of controllability—personal controllability, clinical controllability, and permanence. Thus, we employed three manipulation check questions that participants responded to on 9 ­ point Likert

2 To see whether our naming influenced perceptions of controllability, we computed a composite variable collapsing across language and controllability condition and computed a composite controllability score and a composite stigma score for Grespar and Munder, separately. A paired­samples t test revealed no significant difference of condition name on controllability, t(438) = ­1.19, p = .235. Similarly, we found no significant difference of condition name on stigma, t(437) = 1.18, p = .239.

scales ranging from 1 (strongly disagree_to 9 (strongly agree) to assess whether we successfully manipulated controllability. Each question was adapted to the condition name. The questions were: “How clinically controllable (i.e., drug therapy and psychotherapies) is [Grespar/Munder]?,” “How personally controllable (i.e., individual can take action to address and treat symptoms) is [Grespar/Munder]?,” and “How permanent (i.e., lasting or remaining unchanged indefinitely) is [Grespar/Munder]?” The three questions had good internal reliability ( α = .93); therefore, we computed a controllability manipulation check composite by averaging the three items together. Higher numbers indicate that participants attribute more controllability toward the hypothetical individual. Due to the manipulation of language being more straightforward and face valid, we employed no manipulation check.

Stigma

Stigma was assessed using a modified version of the 26­item Factors and Mental Illness of Stigma Attribution Questionnaire (Brown, 2008). This scale consists of six subscales: Fear (7 items), Help (6 items), Responsibility (3 items), Forcing Treatment (4 items), Empathy (3 items), and Negative Emotions (3 items).

The subscales assess various dimensions of stigma. Fear measures the anxiety or fear individuals feel toward people with mental illness, reflecting concerns about potential danger or unpredictability. Help evaluates participants’ willingness to assist individuals with mental illness, encompassing both emotional support and practical actions. Responsibility gauges the extent

TABLE 1

Descriptive Statistics and Cronbach's Alpha for Stigma Subscale

Fear “How scared of a [Grespar/Munder person or person with Grespar/Munder] would you feel?” 2.64c 1.81 .98

Help “I would be willing to talk to a [Grespar/Munder person or person with Grespar/Munder] about their problems.” 6.66a 1.62 .92

Responsibility “I would think that it is a [Grespar/Munder person or person with Grespar/Munder] own fault that they are in the present condition.”

Forcing Treatment

Empathy

Negative Emotions

“I think it would be best for [Grespar/Munder person or person with Grespar/Munder] community if they were put away in a psychiatric hospital.”

1.85 .77

1.70 .93

“How much sympathy would you feel for a [Grespar/Munder person or person with Grespar/Munder].” 6.62a 1.59 .79

“How irritated would you feel by a [Grespar/Munder person or person with Grespar/Munder].” 2.41d 1.68 .92

Note. M, SD, and α represent mean, standard deviation, and Cronbach's alpha, respectively. Superscripts indicate Bonferroni-adjusted pairwise comparisons, with differing subscripts denoting statistically significant differences. Additionally, negative emotion did not survive the Bonferroni adjustment and is not significant Controllability and Language

to which participants blame individuals with mental illness for their condition. Forcing Treatment examines attitudes toward imposing treatment on individuals with mental illness, even against their will. Empathy captures participants’ emotional understanding and compassion toward individuals with mental illness, while Negative Emotions assesses negative emotional responses, such as anger or disgust, reflecting emotional distance or aversion toward this population (Brown, 2008).

Participants rated each of the 26 items in a random order on a 9­point Likert scale, ranging from 1 (strongly disagree) to 9 (strongly agree). All items were modified to incorporate the language type manipulation (personfirst vs. identity­first) and condition name (Grespar vs. Munder). For example, an original item, “How scared of Harry would you feel?” was modified to “How scared of a [Grespar/Munder person or person with Grespar/ Munder] would you feel?” Example items for each subscale are shown in Table 1.

Composite stigma scores for each subscale were computed by averaging all items within that subscale, following the procedure outlined by Brown (2008). The Help and Empathy subscales were reverse­coded so that, across all dimensions, higher scores indicated greater amounts of stigma. Table 2 presents the mean, standard deviation, and reliability estimates for each subscale.

Procedure

This study was conducted with prior approval from the University of Denver’s institutional review board (IRB# 1329885). After providing informed consent, participants viewed two vignettes, each describing a fictitious mental illness (Grespar or Munder) in a random order. Vignettes featured either high or low controllability descriptions (between­subjects manipulation). One vignette used identity ­ first language, and the other vignette used person­first language (within­subjects manipulation; see Appendix). Which name was paired with which language type was counterbalanced between participants. After reading each vignette, participants completed measures of perceived controllability (manipulation check) and stigma (dependent variable). Participants then completed a demographic questionnaire that included age, gender, race, ethnicity, education, and political orientation items. Lastly, participants were debriefed, thanked, and compensated.

Results

Manipulation Check

We conducted an independent­samples t test to assess the effects of controllability on the manipulation check, which yielded a significant effect, t(437.51) = ­27.36, p < .001, d = ­ 2.60, 95% CI[ ­ 2.83, ­ 2.45]. We found that participants in the low controllability condition

Shaver, Summers, Paganini, and Lloyd | Controllability and Language on Stigma

(M = 4.17, SD = 0.97) rated the hypothetical conditions as less controllable than those in the high controllability condition (M = 6.81, SD = 1.05).

Primary Analysis

To examine the independent and interactive effects of controllability and language on stigmatization, we conducted our primary analysis: a 2 (controllability: high, low) by 2 (language: person­first, identity­first) by 6 (stigma dimension: force treatment, responsibility, help, empathy, negative emotions, fear) mixed­model ANOVA on stigma. Language and dimension of stigma served as repeated factors, and controllability was a between­subjects factor. Of note, the six dimensions of stigma are treated as a repeated factor in the overall mixed model ANOVA. This approach enabled consideration of whether dimension of stigma moderated effects of language or controllability. But just with other factorial designs, when focusing on main effects or interactions that do not involve the stigma dimension (i.e., main effect of language, main effect of controllability, or language by controllability interaction)—we collapse across stigma dimension in interpretation of those main effects or lower order interactions.

We predicted a significant main effect of controllability on stigma, such that participants in the high controllability condition would report greater stigma than participants in the low controllability condition. Counter to our hypothesis, there was no main effect of controllability on stigma, F(1, 435) ~ 0.00, p = .97, ηp2 < .01. High controllability (M = 2.86, SD = 1.10) condition did not differ significantly from low controllability (M = 2.85, SD = 1.26)

We expected a significant main effect of language but remained agnostic regarding whether person­first (compared to identity­first) language would increase or lessen stigma. The analysis yielded a nonsignificant main effect of language on stigma, F(1, 435) = 3.71, p = .06, ηp 2 = .01. Identity­first language (M = 2.83, SD = 1.20) descriptively yielded less stigma than personfirst language (M = 2.87, SD = 1.23).

We did not offer a prediction for a main effect of stigma dimension. However, we did observe a significant main effect of dimension, F(5, 2175) = 53.26, p < .001, ηp2 = .11. All dimensions were coded such that higher numbers indicated more stigma. The pairwise comparisons were Bonferroni adjusted for multiple comparisons and indicated that participants had the highest ratings on reverse ­ coded empathy, which was no different from reverse ­ coded help ( p > .99). Reverse ­ coded help was rated significantly higher than responsibility (p = .002), which was rated significantly higher than fear (p = .002). Fear was rated significantly higher than force treatment (p < .001), which was no different from

negative emotion (p > .99). Important to note that after the Bonferroni adjustment for multiple comparisons, negative emotion is not significant.

Given contradictory effects of controllability on stigma in past research, we theorized that dimension of stigma might moderate the effect of controllability on stigma. Indeed, we observed a significant interaction between dimension of stigma and controllability on stigma F(5, 2175) = 84.54, p < .001, ηp2 = .16. Particularly, within the fear, force treatment, negative emotions, and help dimensions, the low controllability condition (compared to high) yielded more stigma. However, for the empathy and responsibility dimensions, high controllability yielded more stigma than low controllability. See Table 2 and Figure 1 for simple effects statistics. See Table 3 for correlations between stigma dimensions3.

Next, we tested our predicted interaction between language type and controllability on stigma. Within the high controllability condition, we predicted that participants would exhibit greater stigma toward conditions described with identity­first, compared to person­first, language. Within the low controllability condition, we predicted that participants would report less stigma toward conditions described with identityfirst, compared to person­first, language. Counter to our prediction, this analysis yielded a nonsignificant language by controllability interaction effect, F(1, 435) = 0.13, p = .72, ηp2 = .001.

Finally, we had no specific prediction for a 3­way interaction between controllability, language­type, and dimension of stigma as no previous research has explored these variables in tandem. We observed a nonsignificant three­way interaction, F(5, 2175) = 1.06, p = .38, ηp2 = .002.

TABLE 2

3 The size of correlation for responsibility and empathy are smaller in nature than correlation of other dimensions.

Discussion

This study explored the interaction between controllability and language across stigma dimensions, revealing differential impacts based on specific dimensions. Low­controllability conditions were associated with heightened stigma in fear, intention to force treatment, negative emotions, and unwillingness to help. Conversely, high­controllability conditions amplified stigma related to lack of empathy and attribution of responsibility. Importantly, after Bonferroni adjustment, the Negative

Effects of Stigma Dimension x Controllability Interaction

Emotions dimension was found to be nonsignificant. These findings underscore the importance of multidimensional approaches to stigma research, as dimensions evoke distinct responses.

Although significant differences were observed across dimensions, all scores were below 4, suggesting subtle effects. A larger, more diverse sample may reveal stronger patterns. Examining specific dimensions, such as fear versus help, in cultural and institutional contexts could provide deeper insights into mechanisms driving stigma.

The interaction between controllability and stigma dimensions may reflect perceptions of agency and blame. Low­controllability conditions evoke fear and negative emotions due to unpredictability or severity which could increase intentions to force treatment or help. Conversely, high­controllability conditions increase responsibility attributions, reducing fear and negative emotions while fostering empathy through perceived active condition management. These findings suggest interventions addressing controllability perceptions could reduce stigma.

No significant differences were found between identity­first and person­first language. The descriptive pattern while small stands in contrast with previous theories and empirical evidence to suggest that personfirst language is less stigmatizing than identity­first language. One possible explanation for this unexpected pattern in the current study could be the greater fluency of identity­first language within the English language as many communities argue that identity­first language is preferred over person­first language (Wooldridge, 2023). This entrenchment within certain communities could influence stigma, which emphasizes the importance of prioritizing individual language preferences in discussions surrounding mental health. Future research should explore how language preferences influence stigma across different mental health conditions and cultural contexts.

Limitations and Future Directions

The use of hypothetical mental illnesses enhanced internal validity but reduced external validity. Although pretesting ensured neutrality, the believability of condition names was not assessed, which may have influenced participant engagement. Future studies should evaluate the believability of hypothetical conditions and use naming conventions aligned with real diagnoses to improve ecological validity. Manipulating multiple aspects of controllability— such as genetics, symptom management, and treatment responsiveness—limited the ability to isolate their individual effects. Future research should examine these facets separately to clarify their specific impacts on stigma. Cross­cultural studies could also explore variations in controllability perceptions and their influence on stigma dynamics.

FIGURE 1

Simple

Shaver, Summers, Paganini, and Lloyd | Controllability and Language on Stigma

This study assessed attitudes rather than behaviors, which limits its real­world applicability. To address this, future research should incorporate behavioral measures, such as observing discriminatory actions or testing interventions in naturalistic settings. Longitudinal designs could further explore how stigma ­ related behaviors evolve over time, particularly in response to interventions targeting controllability or language use.

Finally, while this study focused on general mental illness stigma, specific conditions may evoke unique stigma dynamics. Future research could explore the role of controllability and language use in conditions like depression, schizophrenia, or substance use disorders, providing insights to tailor interventions. Additionally, examining stigma in clinical versus everyday contexts could inform strategies for both practitioners and policymakers.

Conclusion

Stigma increases healthcare costs, hampers treatmentseeking, and reduces self ­ esteem and employment opportunities (Corrigan, 2004; Henderson et al., 2013; Evans­Lacko et al., 2015). Understanding factors that influence stigma, such as controllability and language, is crucial for developing inclusive policies and best practices for clinicians, educators, and policymakers. This study highlights the significant role of perceived controllability in stigma across dimensions. Low­controllability conditions increased fear, negative emotions, and intentions to force treatment while reducing responsibility and empathy. Language effects were nonsignificant. These findings emphasize the need for multidimensional approaches in stigma research and intervention design.

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Author Note

Claire E. Shaver https://orcid.org/0009-0001-1588-5740

We have no conflicts of interest to disclose. This study was supported by the University of Denver. Special thanks to Kevin Summers, Gina Paganini, E. Paige Lloyd, and Max Weisbuch for the support and mentorship during the distinction program. Correspondence concerning this article should be addressed to 2155 S. Race St., Frontier Hall Denver, CO 80208.

Email: claire.shaver@du.edu

Shaver, Summers, Paganini, and Lloyd | Controllability and Language on Stigma

APPENDIX

Low Controllability, Person-First Vignette. “In this society a subset of individuals have been diagnosed with a mental health disorder called Munder. People with Munder were born with this mental health condition and it tends to persist over time. People with Munder usually inherit risk from biological parents. For people with Munder, their symptoms cannot be easily controlled, and their symptoms are often unresponsive to drug or psychotherapies and lifestyle changes (e.g., sleep, diet).”

Low Controllability, Identity-First Vignette. “In this society a subset of individuals have been diagnosed with a mental health disorder called Grespar. Grespar people were born with this mental health condition and it tends to persist over time. Grespar people usually inherit risk from biological parents. For Grespar people, their symptoms cannot be easily controlled, and their symptoms are often unresponsive to drug or psychotherapies and lifestyle changes (e.g., sleep, diet).”

High Controllability, Person-First Vignette. “In this society a subset of individuals have been diagnosed with a mental health disorder called Munder. People with Munder were not born with this mental health condition instead it tends to develop over time. People with Munder usually do not inherit risk from biological parents. For people with Munder, their symptoms can be easily controlled and their symptoms are often responsive to drug or psychotherapies and lifestyle changes (e.g., sleep, diet).”

High Controllability, Identity-First Vignette. “In this society a subset of individuals have been diagnosed with a mental health disorder called Grespar. Grespar people were not born with this mental health condition instead it tends to develop over time. Grespar people usually do not inherit risk from biological parents. For Grespar people, their symptoms can be easily controlled and their symptoms are often responsive to drug or psychotherapies and lifestyle changes (e.g., sleep, diet).”

Authoritative Parenting Moderates the Association Between Social Media Use and Self-Esteem in Young Adults

Lauren D. Adams1 and Patrick Cooper*2

1 Department of Applied Psychology, New York University.

2 Department of Arts and Sciences, Lynn University

ABSTRACT. Research has suggested that social media use has psychological risks and benefits in adolescents and young adults (see Reid & Weigle, 2014, for an overview). The contradictory results suggest that the link between social media use and psychological outcomes could depend on moderating variables. This study examined whether self­perceived parenting style could be one of these moderators. As part of a more extensive study, young adult college students (N = 338,  Mage = 19.21 years,  SD = 1.72 years) completed questionnaires assessing perceived parenting styles, social media intensity (e.g., felt need to check social media), and self­esteem. The study found that authoritative parenting (i.e., warm parents who set reasonable demands on their children) predicts increased self­esteem for college students who report feeling immersed in Instagram (β = .13, p = .013) and X (β = .17, p = .002) but not Facebook (β = .03, p = .529). Surprisingly, permissive and authoritarian parenting did not moderate any association between social media immersion and self­esteem. The study was limited by using only three primary social media platforms and potential bias as a result of using self­reported surveys. Future directions are discussed.

Keywords: self­esteem, parenting styles, social media, authoritative parenting

For many adolescents and young adults, social media use has become second nature in daily life. A plethora of research has examined the psychological effects that social media has on individuals, and much of it focuses on the dark side of excessive use: poor self­esteem, depression, anxiety, and other mental health issues (Coyne et al., 2020; Faraon & Kaipainen, 2014; Woods & Scott, 2016), especially for image­based platforms (Wright et al., 2020; Wright et al., 2021). Other research has shown that social media use can have positive effects, such as positive identity development and peer interaction (Syed et al., 2020; Uhls et al., 2017).  These mixed findings suggest that the relationship between social media use and psychological outcomes may be influenced by moderating factors. Parenting style, a significant socialization influence throughout childhood and adolescence (Baumrind, 1971), may play a critical role in shaping how young adults interact with social media and experience its effects.

Building on the work of Faraon and Kaipainen (2014) and Woods and Scott (2016), this study focused on college­aged young adults to examine how different

parenting styles moderate the relationship between social media intensity and self­esteem. For instance, a healthy parent–child relationship reduces adolescent motivation to use social media excessively, reducing the risk of low self­esteem and other negative outcomes (Chou & Lee, 2017; Floros & Siomos, 2013). Conversely, children of neglectful or authoritarian parents are more likely to exhibit addictive internet use (Tur­Porcar, 2017). By exploring how different parenting styles moderate the relationship between social media use and adolescent self ­ esteem, results can reveal potential pathways through which parenting influences the social­emotional outcomes associated with social media behaviors.

Social Media Use in Adolescents and Young Adults

Approximately 95% of students have access to the internet (Tur­Porcar, 2017), and 92% of adolescents report using social media daily (Richter, 2018). Furthermore, during the onset and progression of the COVID­19 pandemic, screen time was up as much as 30% (Wright et al., 2023). It is difficult to pinpoint the mechanism behind what makes

social media use “problematic.” As of the writing of this article, there is no proper diagnosis through the Diagnostic and Statistical Manual of Mental Disorders (DSM­V) for problematic social media use. However, an official diagnosis of Gaming Disorder (IGD) could reasonably explain some problematic social media behaviors (see Richter 2018). To be diagnosed with IGD, an individual must exhibit symptoms such as preoccupied behavior, unsuccessful attempts to stop the behavior, and deception of others.

Because many adolescents and young adults have access to and use the internet and social media, excessive social media use could pose a severe risk for these young people. Researchers generally agree that social media use has many negative outcomes, including depressive symptoms (Twenge et al., 2018), decreased happiness or life satisfaction (Kross et al., 2013), and sleeplessness (Woods & Scott, 2016). Excessive social media use is also associated with decreased self­control, increased sensation­seeking, and increased anger or frustration (Zhang et al., 2015). This aligns with the fact that the prefrontal cortex, essential in executive functioning (e.g., planning and emotional regulation), has not fully developed until the mid­to late­20s (Arain et al., 2013). There are social­cognitive consequences to excessive social media use as well. Many young adults suffer from fear of missing out (FOMO; Gupta & Sharma, 2021). Some research has suggested that social media abuse, and more broadly, internet addiction, is associated with lower self­esteem in adolescent girls but not boys (Richter, 2018). By the time these adolescents reached adulthood, all participants who exhibited social media abuse had lower self­esteem.

Overall, the research on gender differences in social media use has revealed varying patterns influenced by unique motivations and platform choices. Women often use social media for relationship­building and social interactions, whereas men predominantly use it for information gathering (Krasnova et al., 2017). Moreover, susceptibility to internet addiction differs by gender; men are more prone to gaming addiction, and women are more likely to develop social media addiction (Su et al., 2020). These findings highlight the complexity of gender dynamics in digital behaviors, which are further complicated by factors such as platform choice, geographic location, socioeconomic status, and age. The current study elected to control for gender in analyses rather than examine it as a moderator. This decision reflects the primary focus on social media intensity and parenting styles, allowing for a more parsimonious exploration of these relationships.

Specific Social Media Platforms: Different Purposes, Different Effects

As of 2024, the average internet user has seven different

social media accounts, and Facebook was approaching three billion unique users, two billion Instagram users, and 611 million X users (Kepios, 2024). Users are attracted to various social media platforms for their distinct social opportunities, suggesting that the effects of social media use are not uniformly negative, as different platforms offer unique outcomes (Wright et al., 2020). As seen in platforms such as LinkedIn, motivation to engage with others for professional reasons might lead to higher positive affect, subjective social status, peer support, and lower loneliness. There might be a few social benefits, such as feeling more peer support or social integration for image­based platforms like Snapchat and Instagram. However, there are also documented negative effects of these image ­ based platforms (Wright et al., 2020). The critical component here is that platform and purpose matters. The platform sets the basis for how users interact with each other and, ultimately, how they are affected by social media use. Facebook  It is no surprise that Facebook is the most researched social media platform, as it is one of the world›s oldest and still most widely used platforms (Kepios, 2024; Sidoti, 2024). Excessive Facebook use is associated with an increased risk of depression in adolescents, mostly because of increased opportunities for social comparison, leading to envy, depression, and low self ­ esteem (Appel et al., 2016; Lin et al., 2016 ; Vogel, et al., 2014). However, Jaidka (2022) argued that Facebook’s more accessible access to self­disclosure when signing on, as exemplified by the “What is on your mind?” prompt in the top center of the page, encourages self­disclosure instead of social comparison. This is not a feature on image­based platforms, whose purpose is to document experiences through pictures and text communication, which is limited and hidden away.

With the affordances to contact friends being hidden away, Instagram makes the user’s experience more isolated and passive—an indicator of harmful social media use predictive of lower well­being. (Jaidka, 2022, p. 7).

Consequently, in a geospatial analysis of social media use from 2016–2018, Jaidka (2022) found that Facebook use positively impacts well­being, especially in higher income populations.  In contrast, Instagram and X had a negative impact. Furthermore, these effects are seen in specific groups, with lower income and often Black communities at greater risk for the adverse effects of Instagram use.

Instagram.  Instagram and other image ­ based platforms provide an ideal medium for social comparison, which can lead to fluctuations in self­worth through constant reappraisals of the self as compared to

others (Festinger, 1954). Many users are drawn to the fact that Instagram is an image­based platform wellsuited for quick access to many photos and photo­based stories. Therefore, users are less likely to use the platform for social interaction (Alhabash et al., 2017) than for social comparison.

The research on the well­being effects of Instagram use is mixed. Using Instagram for surveillance of others, social comparison, or “coolness” is associated with increased narcissism, whereas this might not be the case for individuals who use it for creativity or documentation purposes (Sheldon & Bryant, 2016). Additionally, when self ­ worth is contingent on gaining approval from others, excessive Instagram use is associated with lower self­esteem. This effect is not seen when users develop a sense of self­worth from other means (Stapleton et al., 2016). Conversely, compared to nonusers, Instagram users report higher social integration and peer support, especially for college students. Wright et al. (2020) argued that, because college students tend to use the internet extensively, using many social media platforms, including Instagram, may “increase perceptions of peer acceptance and provide them with topics to discuss with peers during in­person interactions” (p. 19). Therefore, because of the mixed well­being effects of Instagram use, it is necessary to examine potential interactive factors that contribute to users’ well­being.

X. Formerly known as Twitter, X provides users with quick connections through short communications, often text­based, but also through link­sharing, pictures, and videos. As a means of quick exchange of information, many individuals use X for information ­ gathering and dispersing purposes, as well as social interaction (Johnson & Yang, 2009). Through the use of hashtags, X is a medium well ­ suited to share ideas regarding virtually any topic. In discussing mental health, Berry et al. (2017) found that the most common reason people tweet was to build a sense of community through raising awareness about mental health disorders. However, because of increased public discourse, some researchers found that X use is associated with increased negative outcomes such as political polarization, outrage, and decreased overall self­perceived well­being (de Mello et al., 2022). X use is also associated with increased depression (Zhang et al., 2021) and loneliness (Ye et al., 2021) in adults, especially when users tweeted more or combined use with other platforms.

Summary. Although people use different social media platforms for varying purposes—whether maintaining relationships on Facebook or engaging in image ­ based social comparison on Instagram and X—the effects of these platforms on self­esteem remain inconsistent. Research indicates that, although

some users experience positive outcomes such as social support and community engagement, others report lower self­esteem and increased social comparison. This disparity suggests that the relationship between social media intensity and well­being is not straightforward and may vary across platforms. Thus, this study sought to explore the direct associations between Facebook, Instagram, and X intensity and self­esteem, with a focus on understanding how these platforms may differentially impact users’ self­perceptions.

Parenting Styles and Well-Being

Baumrind (1971) suggested that parenting style varies on two dimensions: the degree of warmth and the degree of control exerted on a child. Authoritative parents provide both warmth and reasonable control of their children. Through consistent discipline and a warm approach, these parents provide a foundation for healthy relationships for their children (Kurdek & Fine, 1994; Morris et al., 2021). Children of authoritative parents develop a sense of trust and are more likely to listen and internalize their parents’ demands. Because of this, these children often do better in school (Steinberg et al., 1992) and in coping with stress (Floros & Siomos, 2013; Silva et al., 2007). Children also reap the benefits of authoritative parenting as they reach adolescence and early adulthood, as their peers become significant socialization agents. For adolescents, authoritative parenting behaviors such as parental monitoring (Brown & Bakken, 2011) and emotional support (Morris et al., 2017) are associated with higher academic achievement and better social relationships with peers (Lamborn et al., 1991; Steinberg et al., 1992).

In contrast, authoritarian parents exhibit strict control and show little warmth. Permissive parents exhibit low control and high warmth. Neglectful parents offer low control and low warmth. On average, children who experience authoritarian, permissive, or neglectful parenting are at risk for maladjustment (Pinquart, 2017; Silva et al., 2007), but it is important to note that many of these effects are dependent on both cultural differences and socioeconomic status (SES; Sorkhabi & Mandara, 2013). For example, children in low­SES communities are more likely to benefit from authoritarian parenting, though not as much as they would benefit from authoritative parenting (Dearing, 2004). Furthermore, because permissive parenting provides a sense of warmth and authoritarian parenting provides a sense of control, some children might see some positive effects on their well­being. Therefore, it is debated how nonauthoritative parenting styles directly affect adjustment because of these other factors.

Summary. Research on parenting styles consistently

shows that the way parents balance warmth and control significantly influences the well­being of their children. Authoritative parenting, characterized by high levels of warmth combined with clear structure and guidance, is strongly associated with higher self ­ esteem and better emotional outcomes in children and young adults (Steinberg et al., 1992). In contrast, authoritarian parenting, which emphasizes control but lacks warmth, often leads to lower self­esteem and negative emotional development (Pinquart & Gerke, 2019). Permissive parenting, which provides warmth but lacks structure, presents more mixed outcomes: While the emotional support permissive parents provide could foster selfesteem, the lack of clear boundaries and guidance may also hinder emotional regulation and personal growth. As such, this study examined how these different parenting styles directly associate with self­esteem in a college­aged population.

Study Rationale

This study replicated key findings from previous work (Faraon & Kaipainen, 2014; Vogel et al., 2014; Woods & Scott, 2016) while also extending the literature by exploring how parenting styles moderate the relationship between social media use and self ­ esteem in a college­aged sample. Although earlier studies focused on different age groups or outcomes such as well­being, our research applied these findings to a new demographic and psychological variable, thus broadening the understanding of this relationship.

Knowing that both parents and social media can impact social­emotional development (e.g., selfesteem), it is reasonable to believe that the quality of the parent–child relationship could buffer or exacerbate the effects of social media use. Of particular interest, a high­quality parent–child relationship may boost positive social media use and reduce the risk of developing low self­esteem and other maladaptive outcomes (Chou & Lee, 2017; Floros & Siomos, 2014; Hwang et al., 2017; Lee et al., 2022; Ren & Zhu, 2022). Furthermore, authoritative parenting helps children develop healthy emotional responses to stress and creates a template for developing healthy peer relationships, something that social media may or may not provide (Steinberg, et al. 1992). Therefore, there are several mechanisms through which parenting styles may exhibit moderating effects.

Authoritative parenting, characterized by warm and responsive interactions, enhances adolescents’ abilities to effectively regulate their emotions. This skill is helpful in helping adolescents navigate the emotional challenges that arise from social media use, such as dealing with negative feedback and social comparison (Eastin et al., 2006). Additionally, parental monitoring

strategies are crucial, including setting boundaries around social media use, engaging in discussions about online content, and sharing media experiences. These practices help in shaping healthier social media habits and attitudes, mitigating risks such as cyberbullying or excessive use. Moreover, authoritative parents model effective communication and provide emotional support, equipping their children with the social skills necessary to navigate both online and offline relationships positively. Adolescents who develop such social competence are better prepared to form meaningful connections and are less likely to be negatively impacted by social media. Conversely, children of nonauthoritative parents are more likely to exhibit problematic social media use (Tur­Porcar, 2017). This contrast underscores the potential for authoritative parenting to buffer and poor parenting to exacerbate the challenging aspects of social media engagement. Specifically, nonauthoritative parenting styles often fail to support the development of emotional regulation, offer ineffective parental monitoring, and do not effectively foster social competence. Without these critical skills, adolescents may struggle to manage the emotional and social challenges presented by social media, potentially leading to heightened stress and lower self­esteem. These parenting styles, characterized by less communication and emotional support, leave adolescents ill­equipped to navigate the complex social dynamics of online interactions and more vulnerable to the negative effects of social media exposure.

Current Study

This study examined how social media intensity on three platforms—Facebook, Instagram, and X—relates to self­esteem in college­aged young adults, while also investigating how these relationships may be moderated by different parenting styles (authoritative, authoritarian, and permissive). Previous research has suggested that increased social media intensity, regardless of the platform, is often associated with lower self­esteem due to the role of social comparison (Faraon & Kaipainen, 2014; Woods & Scott, 2016). In particular, Facebook intensity has been linked to lower self­esteem through increased social comparison (Vogel et al., 2014), and similar effects have been observed for Instagram and X. We hypothesized (H1) that higher intensity of use on all three platforms—Facebook, Instagram, and X—would be negatively associated with self­esteem.

Beyond social media use, this study also investigated how parenting styles influence self­esteem. Authoritative parenting, characterized by warmth and structure, is consistently associated with higher self ­ esteem (Pinquart & Gerke, 2019; Steinberg, 1992). In contrast, authoritarian parenting, which emphasizes control and

lacks warmth, tends to lower self ­ esteem, while the effects of permissive parenting are less clear due to the combination of warmth without sufficient structure. We hypothesized (H2) that authoritative parenting would be positively associated with self­esteem, authoritarian parenting would be negatively associated with selfesteem, and permissive parenting would show a weaker or mixed association with self­esteem.

Finally, we explored how parenting styles may moderate the relationship between social media intensity and self­esteem. We hypothesized (H3) that authoritative parenting would buffer the negative effects of high social media intensity on platforms like Facebook, Instagram, and X, as such parenting provides emotional support and structure that helps individuals navigate the challenges of social comparison and online feedback (Pinquart & Gerke, 2019; Steinberg, 1992). In contrast, we expected that neither authoritarian nor permissive parenting would significantly moderate the relationship between social media use and self­esteem, as these parenting styles do not provide the necessary emotional regulation and support to mitigate the negative effects of social media (Pinquart & Gerke, 2019).

Method

Participants

College students were recruited from two southeastern United States universities, either directly in public campus areas or via trained research assistants who administered the survey in classrooms. Of the 374 individuals who took the survey, 338 met the manipulation check criteria and were included in the final analysis. The participant pool consisted of 219 women and 118 men, with an average age of 19.21 years (SD = 1.72). It is important to note that 57 participants did not report their age. Ethnic breakdown was as follows: 14.83% Black/African American, 5.04% Asian American/Pacific Islander, 51.03% White/European American, 19.88% Hispanic/Latino, and 9.19% did not respond. There was no other missing data for the variables in this study. All participants were entered into a raffle for one of ten $50 gift cards for their participation. Ethical approval was secured from the institutional review boards (IRB) at both institutions to ensure adherence to ethical standards. All participants provided informed consent before participating.

Materials Parenting Styles

Participants completed three questionnaires as part of a larger study. The first was the Parental Authority Questionnaire (PAQ; Buri, 1991), a 30 ­ item measure designed to assess self ­ perceived parenting styles. Specifically, participants were

asked to respond about their “parents” as a whole, as opposed to their mother or father specifically. Responses ranged from 1 ( strongly disagree ) to 5 ( strongly agree ). The PAQ includes three 10 ­ item subscales that measure authoritative, authoritarian, and permissive parenting styles, but it does not assess neglectful parenting. Composite scores were computed by averaging the scores for all 10­items of each subscale. This omission aligns with Baumrind’s (1971) original classification of parenting styles, with the neglectful style later introduced by Maccoby and Martin (1983). The PAQ was chosen due to its frequent citation and use in assessing parenting styles. Reliability for all subscales was acceptable: authoritative parenting ( α = .83), authoritarian parenting ( α = .82), and permissive parenting (α = .72).

Social Media Intensity

The second measure was an adapted 18­item version of the Social Media Intensity Scale (Ellison et al., 2007), applied to three platforms: Facebook, Instagram, and X (formerly Twitter). Each platform was assessed using six items, with example items including, “Facebook is part of my daily routine” and “I feel out of touch when I have not logged onto Instagram for a while.” Responses were provided on a 5­point scale, ranging from 1 (strongly disagree) to 5 (strongly agree). Composite scores were computed by averaging the scores for all six items. Reliability was also acceptable for all subscales: Facebook intensity (α = .89), Instagram intensity (α = .91), and X intensity (α = .96).

Self-Esteem

The third measure was the Rosenberg Self­Esteem Scale (Rosenberg, 1965), which consists of 10 items assessing global self ­ esteem. Responses were measured on a 5­point scale from 1 (strongly disagree) to 5 (strongly agree ). Sample items include “On the whole, I am satisfied with myself” and “I feel that I have a number of good qualities.” This scale demonstrated acceptable reliability (α = .79).

Procedure

Participants were recruited as part of a larger study and were asked to complete the questionnaire at a time convenient to them. After providing informed consent, participants were presented with the three questionnaires described in the Materials section. The study was conducted online, allowing participants to complete the survey in a comfortable environment of their choosing. Each questionnaire was administered sequentially, starting with the Parental Authority Questionnaire, followed by the Social Media Intensity

Scales, and concluding with the Rosenberg Self­Esteem Scale. On average, participants took 15–20 minutes to complete the entire set of measures. Data collection was anonymous, and no identifying information was linked to participants’ responses.

Data Analysis

All statistical analyses, including descriptive statistics, correlations, and multiple regression, were conducted using SPSS version 21. All variables were standardized prior to analysis to ensure comparability and interpretability of the results. Interaction effects were probed using procedures prescribed by Aiken and West (1991). Additionally, graphical representations were created using Microsoft Excel, as outlined by Dawson (2014). Because men and women exhibit different motivations for using social media (Krasnova et al., 2017), and the primary aim of this study was to examine how parenting styles moderate the relationship between social media use and self­esteem, gender—which could act as a confounding variable—was controlled for in all analyses.

Results

The means and standard deviations of all measures can be seen in Table 1. Note that there was a gender difference in several measures. Women were coded as “0,” and men were coded as “1.” Specifically, women scored higher in X intensity, t (335) = 2.13,  p  = .03,  d  = 0.24, and Instagram intensity, t (335) = 2.17,  p  = .03,  d  = 0.25, whereas men reported higher selfesteem, t(335) = ­4.53,  p  < .001,  d  = ­0.58. There were no gender differences in Facebook intensity or any of the parenting variables.

H1

To examine H1, which stated that Facebook intensity, Instagram intensity, and X intensity would be negatively associated with self­esteem, three separate multiple

regression models were computed. After standardization and in Step 1, age and gender were entered as controls. In Step 2, one social media intensity variable was entered. The dependent variable was self­esteem. For the model that included Facebook intensity, results indicated that the predictors accounted for 3.8% of the variance, R2 = .04, F(3, 270) = 3.54, p = .015. Facebook intensity was negatively associated with self­esteem (β = ­.16, p = .008). For the model that included Instagram intensity, results indicated that the predictors accounted for 4.1 % of the variance, R2 = .041, F(3, 271) = 3.86, p = .010. Instagram intensity was also negatively associated with self­esteem (β = ­.17, p = .005). For the model that included Instagram intensity, results indicated that the predictors accounted for 2.6 % of the variance, R2 = .03, F(3, 271) = 2.42, p = .07. X intensity was not associated with self­esteem (β = .12, p = .055), however this effect is trending.

An additional hierarchical multiple regression model was computed to examine the effects of all three social media intensity variables together. In Step 1, age and gender were entered as controls. In Step 2, Facebook intensity, Instagram intensity, and X intensity were entered. The results indicated that the three predictors accounted for 9.7% of the variance, R2 = .10; F(5, 268) = 5.78, p < .001). Of the three independent variables, only Facebook intensity predicted self­esteem, β = ­.30, p < .001, however X intensity was trending, β = .22, p = .05.

H2

To examine H2, which stated that authoritative parenting would be positively associated with self ­ esteem, authoritarian parenting would be negatively associated with self­esteem, and permissive parenting would show a weaker or mixed association with self­esteem, three separate multiple regression models were computed. In Step 1, age and gender were entered as controls. In Step 2, one parenting variable was entered. The dependent variable was self­esteem.

TABLE 1

Means, Standard Deviations, and Correlations Between All Measures

1. Authoritative Parenting

2. Authoritarian Parenting

3. Permissive Parenting

4. Facebook Intensity

5 X Intensity

6. Instagram Intensity

7. Self-Esteem

Note * p < .05. ** p < .01. *** p < .001. All correlations are controlling for age and gender (Women = 0, Men = 1). Values in brackets indicate 95% confidence intervals for each correlation coefficient. Confidence intervals for partial correlations were estimated using bootstrapping with 1000 samples.

Authoritative Parenting and Social Media | Adams and Cooper

For the model that included authoritative parenting, results indicated that the predictors accounted for 32.6% of the variance, R2 = .33; F(3, 271) = 43.60, p < .001. Authoritative parenting was positively associated with self­esteem (β = .56, p < .001). For the model that included authoritarian parenting, results indicated that the predictors accounted for 4.8 % of the variance, R2 = .05; F(3, 271) = 4.57, p = .004). Authoritarian parenting was positively associated with self­esteem (β = .19, p = .002). For the model that included permissive parenting, results indicated that the predictors accounted for 6.7% of the

Instagram Intensity Was Associated With High Self-Esteem for Those With Authoritative Parents.

variance, R2 = .07; F(3, 271) = 6.44, p < .001). Permissive parenting was positively associated with self­esteem (β = .23, p < .001).

An additional hierarchical multiple regression model was computed to examine the effects of all three parenting variables together. In Step 1, age and gender were entered as controls. In Step 2, authoritative parenting, authoritarian parenting, and permissive parenting were entered. The results indicated that the three predictors accounted for 34% of the variance, R 2 = .03; F (5, 269) = 27.72, p < .001. Of the three independent variables, only authoritative parenting (β = .54, p < .001) and permissive parenting (β = .13, p = .016) predicted self­esteem.

H3

Hierarchical multiple regression analysis was conducted to explore the moderating effects of three selfperceived parenting styles (authoritative, authoritarian, and permissive) on the relationship between social media usage intensity across three platforms (Facebook, Instagram, and X) and self ­ esteem. The analysis proceeded in three steps: Step 1 included gender as a control variable; Step 2 assessed the main effects of social media intensity and parenting styles; and Step 3 investigated the interactions between each parenting style and social media intensity.

Authoritative Parenting

X Intensity Was Associated With High Self-Esteem for Those With Authoritative Parents.

There were nine potential interactive effects, three of which were our focal hypothesis in H3. In short, we hypothesized that authoritative parenting would boost the self­esteem of those who score high on social media intensity. H3 was partially supported. Authoritative parenting moderated the association between Instagram intensity and self­esteem, R2 =  .12,  F(4, 326) = 11.22, p < .001, with a significant interaction term (β  = .13,  p = .013). Follow­up simple slopes analyses (Aiken & West, 1991) showed that high Instagram intensity is associated with high self­esteem, but only for participants who reported high authoritative parenting (β  = .30,  p < .001). See Figure 1 for a plot of the interactive effect.

Authoritative parenting also moderated the association between X intensity and self­esteem, R2 = .10,  F(4, 309) = 8.62, p < .001, with a significant interaction term (β = .17, p = .002). The results of follow­up simple slopes analyses (Aiken & West, 1991) showed that high X intensity is associated with high self ­ esteem, but only for participants who reported high authoritative parenting (β  = .30,  p  < .001). See Figure 2 for a plot of the interactive effect.

Authoritative Parenting

Although the overall model was significant for Facebook, R 2 =  .10,  F (4, 309) = 8.62, p < .001, the interaction term was not (β  = .03,  p  = .53). In other words, authoritative parenting did not moderate the

FIGURE 1

FIGURE 2

association between Facebook intensity and self­esteem. See Figure 3 for a plot of the (lack of) interactive effect. Furthermore, we found no significant effects in our analysis examining whether authoritarian and permissive parenting moderated the social media self­esteem link. See Tables 2–4 for a summary of the analyses.

Discussion

Previous research has suggested that there are psychological risks and benefits of social media use in young adults. The mixed results indicate that there are potential moderators affecting the link between social media use and a healthy sense of self. The primary purpose of this study was to examine whether self­perceived parenting style moderated the association between social media intensity and selfesteem. We found that young adults can develop a high sense of self­esteem when they feel an intense desire to stay connected to Instagram and X, especially when they have authoritative parents. This effect was not seen for Facebook, nor was it seen for participants who perceive their parents as authoritarian or permissive. Here, we discuss the results for each hypothesis in turn.

H1 Was Partially Supported

Our hypothesis (H1) that Facebook, Instagram, and X intensity would be negatively associated with self­esteem received partial support. The results indicated that Facebook and Instagram intensity were significantly associated with lower self­esteem, consistent with prior research that links excessive social media use to negative self­perceptions through mechanisms such as social comparison (Vogel et al., 2014). Specifically, higher Facebook intensity was associated with lower self­esteem, and higher Instagram intensity also predicted lower self­esteem.

However, X intensity did not show a significant relationship with self­esteem, though the result trended toward significance. This finding suggests that the nature of engagement with X may not provoke the same degree of social comparison or affect self­perception as strongly as platforms like Facebook and Instagram, which are more image­driven. These results echo earlier studies suggesting that platforms designed for visual self­presentation, like Instagram, might intensify social comparison and lower self­esteem, whereas platforms like X may serve more informational or social interaction functions without directly affecting self­worth (Johnson & Yang, 2009; Zhang et al., 2021).

It is important to note that, when all three social media platforms were examined together in a combined model, only Facebook intensity remained a significant predictor of lower self ­ esteem, suggesting that the negative effects of Facebook use may overshadow the impacts of other platforms. These findings support

the idea that social media effects on self­esteem vary depending on the platform and the type of interaction it encourages. Future research should continue to explore the platform­specific nuances of social media use and self ­ esteem, especially for platforms that emphasize different forms of content sharing and engagement.

FIGURE 3

Facebook Intensity Was Associated With High Self-Esteem for Those With Authoritative Parents.

Authoritative Parenting

TABLE 2

Regression Analyses Predicting Self-Esteem From Interactions of Facebook Intensity and Parenting Styles

H2 Was Partially Supported

Our hypothesis (H2) that authoritative parenting would be positively associated with self ­ esteem, authoritarian parenting would be negatively associated with self­esteem, and permissive parenting would show a weaker or mixed association with self­esteem was partially supported.

As anticipated, authoritative parenting was strongly linked to higher self­esteem. This finding aligns with a large body of research indicating that the combination of warmth and reasonable control helps foster self­worth and autonomy in young adults. Authoritative parents provide emotional support and consistent guidance, which create an environment conducive to building positive self­esteem.

Contrary to expectations, authoritarian parenting was also associated with higher self­esteem, which challenges the typical understanding that strict control without warmth is detrimental to emotional development. It is possible that, in certain contexts, the structure and discipline provided by authoritarian parents offer a sense of security and stability that can boost self­esteem. This suggests that the relationship between authoritarian parenting and self­esteem may vary depending on cultural, social, or familial factors.

Permissive parenting, characterized by high warmth

TABLE 3

Regression Analyses Predicting

but low control, was also positively associated with self­esteem, though to a lesser degree than authoritative parenting. The emotional support offered by permissive parents likely contributes to a positive sense of self­worth. However, the lack of clear boundaries and structure may limit the development of emotional regulation and personal responsibility, which could explain why the impact of permissive parenting on self­esteem is not as strong as that of authoritative parenting.

When all three parenting styles were considered together, authoritative parenting remained the most influential factor in predicting self ­ esteem, while permissive parenting also continued to have a smaller but meaningful positive effect. This reinforces the importance of warmth and emotional support across parenting styles, while also highlighting the critical role that authoritative parenting plays in fostering higher self­esteem in young adults.

H3 Was Partially Supported

Our hypothesis (H3) that authoritative parenting would moderate the relationship between social media intensity and self ­ esteem was partially supported. Specifically, we found that authoritative parenting enhanced the positive effects of Instagram and X use on self­esteem, but this effect was not observed

TABLE 4

Regression Analyses Predicting

From Interactions of

for Facebook. These results suggest that authoritative parenting, which combines warmth with reasonable guidance, helps young adults navigate the potential challenges of social media and leverage these platforms for positive self­perceptions.

For Instagram and X, young adults who reported high levels of authoritative parenting experienced higher self­esteem when they were heavily immersed in these platforms. This may be because authoritative parents foster emotional regulation and provide a supportive framework that helps their children manage the risks associated with social comparison and online feedback, particularly on platforms like Instagram and X where self­presentation and social interaction are central. The positive influence of authoritative parenting likely buffers young adults from the potential negative effects of social media use, allowing them to feel more confident and secure in their online interactions.

However, no significant moderating effect was found for Facebook. This could be due to the nature of Facebook as a platform that is more focused on maintaining connections with familiar people, rather than creating new relationships or engaging in social comparison to the same extent as Instagram or X. As a result, the benefits of authoritative parenting may be less relevant when it comes to Facebook use, as reconnecting with known individuals may not present the same social and emotional challenges.

In addition, we found no evidence that authoritarian or permissive parenting styles moderated the relationship between social media intensity and self­esteem. This suggests that the structure and warmth provided by authoritative parenting are unique in fostering resilience to the pressures of social media, whereas authoritarian and permissive parenting styles do not seem to provide the necessary emotional tools to mitigate the risks associated with high social media use.

Potential Limitations and Future Research

Dimensions of Social Media Use

This study examined whether parenting impacts the link between self­reported intensity of social media use and self­esteem. Intensity was measured using a social media intensity scale, which allows researchers to tap into self ­ perceptions of how social media is integrated into one’s day­to­day life. Overall social media use (e.g., time spent on social media) was not measured. The benefit of using the social media intensity scales is that it still captures self­perceptions of use even if a platform is used rarely or never. The primary drawback is that measuring self­perceptions will not capture how much time users actually spend on a platform, which could have negative effects not captured there. Future

research should examine how time spent on social media impacts the effects seen here, as one could still feel immersed in social media but not spend a lot of time on it, and vice­versa.

Furthermore, future researchers could focus on the motivation for social media use and self­esteem. For instance, if a person wants to feel connected to a community on a social media platform, do they reap the benefits of social support regardless of the platform itself? Various motivations for using any platform often overlap, so perhaps the incentive to use a platform is more important than the platform itself. Furthermore, social media is evolving rapidly. The nuanced differences in interacting with platforms might impact the relationships found in this study. For instance, TikTok and Snapchat were the fastestgrowing social media platforms from 2020 through 2022 (Statista, 2023). To further investigate the implications of components of these platforms’ attention, if different motivators would be seen for TikTok, and what of these implications would be seen interacting with new platforms, another study would need to be conducted.

Measuring Direct Parenting Behaviors

Pinquart and Gerke (2019) suggested that permissive parenting is associated with higher self­esteem when it directly measures parenting warmth, suggesting that any level of warmth would contribute to better outcomes for children. Because there are mixed results for researchers who try to establish whether there is a link between parenting style and self­esteem, researchers should ensure that parental warmth and parental control are measured in a way that parcels out their individual effects. Further, researchers should account for cultural and SES­dependent differences in responses to parental warmth and control, as this could add to the nuanced picture of how parenting and social media use interactively contribute to self­esteem.

One limitation of the current study is the omission of neglectful parenting, one of the four parenting styles commonly examined today. Although the Parental Authority Questionnaire (Buri, 1991) captured authoritative, authoritarian, and permissive styles, it did not explicitly assess neglectful parenting, which is characterized by low warmth and low control. Neglectful parenting is known to be associated with adverse outcomes, such as low self­esteem and problematic social media use (Tur­Porcar, 2017). Including this style could have provided a more comprehensive understanding of how various parenting approaches influence the relationship between social media use and self­esteem. Future researchers should consider including neglectful parenting in their assessments to explore its potential

moderating effects on social media use and psychological outcomes, as it may offer additional insights into maladaptive behaviors in digital contexts.

Beyond Self-Esteem

Self­esteem is only one component of personal development. Future researchers should ask how parenting styles and social media use impact other elements of socioemotional development, notably academic achievement and friendship quality (Morris et al., 2021; Steinberg et al., 1992). There seems to be an established relationship between parenting, social media, and academic achievement. For example, in a sample of 1,459 younger adolescents, high­quality mother–child communication moderated the negative association between Facebook, X, Instagram, and Snapchat use and academic achievement (Gordon & McCauley­Ohannessian, 2023). These effects have been corroborated by other studies as well (Hassan et al., 2022; Prabandari & Yuliati, 2016).

Because social media promotes connectedness, parenting styles ostensibly should moderate the association between social media use and friendship quality. Luijten et al. (2022) found that friendship quality moderates the link between social media use and well­being, primarily for women. Could it be that social media use boosts the quality of friendships for young adults who experience authoritative parenting? Perhaps authoritative parenting provides a template for online and offline friendships. Furthermore, although these social media platforms connect individuals, the types of connections are not clearly defined. For instance, do frequent interactions between friends or followers enhance friendship quality? Or, perhaps providing a medium for social support enhances the quality? Angelini et al. (2022) suggested that, because social media platforms offer more availability to friends, these users are more likely to report a sense of instrumental support and companionship. Also, because social media interactions can be asynchronous, meaning that many reactions are not immediate, conflict resolution is fundamentally changed, and perhaps for the better, as temporal distance can diminish potential negative emotional reactions to conflict (Nesi et al., 2018)

Bidirectional Effects and Self-Report Biases

Although self­report surveying is probably the most common way to measure self­perceptions of parenting and social media use, the relationships found here could be further validated through more objective measures. For instance, some research protocols have independent raters rate situational characteristics of social media posts and photos. This would increase interrater reliability and provide some objectivity

to the intensity of social media use. Furthermore, parenting can be measured through direct observation or parent reports of parenting style. This method has challenges as many older adolescents and young adults live outside the home (e.g., college or military). Experimental methods could be employed as well. For instance, researchers could develop and utilize “media ­ specific” parenting programs to examine specific parenting practices employed while children are on social media. It is unclear whether the effects of media­specific authoritative parenting styles benefit children more than a general pattern of authoritative parenting. Furthermore, the cross­sectional nature of this study limits causal conclusions. It might be that those with high self­esteem already seek out Instagram and X to maintain their sense of self­worth, especially when they feel supported by their authoritative parents. Longitudinal analyses can control for these effects to help establish at least some causal inferences.

Conclusions

Social media is omnipresent, and there are risks and benefits to youth immersed in it. Authoritative parenting, characterized by a high degree of warmth and control, buffers the risk of low self­esteem for those fully immersed in Instagram and X. These findings are essential for parents facing the inevitable challenge of managing their children’s social media use. Furthermore, researchers and practitioners can use this information to inform best practices for parenting in the ever­changing online community.

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Author Note

Lauren D. Adams https://orcid.org/0009­0003­6724­1722

Patrick Cooper https://orcid.org/0000­0002­9306­8586

We have no known conflict of interest to disclose.

Positionality Statement: Lauren identifies as a heterosexual, cisgender White woman. Patrick Cooper identifies as a heterosexual, cisgender White man. All authors are nondisabled and acknowledge that their perspectives are influenced by their positions within these dimensions of identity.

Correspondence concerning this article should be addressed to Lauren D. Adams, 1166 Lakes Road, Monroe, NY, 10950, United States. Email: LDA8277@nyu.edu and/or laaurenaadams@gmail.com or by phone at (845)­706­9844.

Protected or Prone? Prescription Drug Misuse in Honors Program College Students

C. Veronica Smith*, Emily E. Haupt, and Lauren N. Jordan* Department of Psychology, University of Mississippi

ABSTRACT. Although research has examined prescription drug misuse (PDM) behaviors and motivations among college students, few studies have investigated these issues among the academically gifted affiliated with honors programs. Students affiliated with honors programs may be more likely than unaffiliated/nonhonors students to engage in PDM due to increased academic strain (Agnew, 1992) or less likely due to increased support offered by their honors programs (Hirschi, 1969). The present study examined prevalence rates of PDM and motives for multiple prescription drug types between honors and nonhonors students in a stratified random sample of college students at a large public university (N = 588). Honors students did not differ in their PDM prevalence compared to nonhonors students (ps ≥ .07, Cramer’s Vs ≤ .08) but were less likely to report motives related to improving grades (p ≤ .001, Cramer’s V = .24) and getting high (p = .04, Cramer’s V = .15). The results contribute to our understanding of the role that honors programs play in supporting gifted college students.

Keywords: prescription drug misuse (PDM), honors students, motivations, general strain theory, social control theory

Prescription drug misuse (PDM) is the use of prescription drugs that are (a) not taken as medically directed (e.g., taking higher doses than prescribed, taking to get high or for purposes other than those prescribed) or (b) taken without a prescription (i.e., taking prescription drugs prescribed to someone else; National Institute of Drug Abuse, 2018). The National Survey on Drug Use and Health estimated that 18 million people aged 12 and older (about 6% of this age group) misused prescription drugs at least once in 2017 (SAMHSA, 2018). Because prescription drugs are recommended to others by doctors, many people falsely believe that using them without a prescription is safe. However, PDM is associated with many potentially dangerous mental, physical, and emotional repercussions (Ali et al., 2015; Holloway et al., 2014; National Drug Intelligence Center, 2006).

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PDM Among College Students

College students appear to be especially susceptible to PDM, as studies using these samples report prevalence rates anywhere from 4% to as high as 43% in samples (Benson et al., 2015). The College Prescription Drug Study anonymously surveyed 19,539 students from 26 institutions across the United States and found that 22.6% had misused one of three types of prescription drugs (i.e., pain medications, sedatives, and stimulants; Phillips & McDaniel, 2018). Further, the initiation of most PDM occurs during college: 65% of those who misused stimulants, 52% of those who misused sedatives, and 39% of those who misused pain medications began misusing in college. Although stimulants are typically the most studied type of prescription drugs, other prescription drugs are misused by college students as well. In fact, Arria and colleagues (2008) assessed PDM in a large group of students during the summer

before their first year of college and once again during their second year of college. The researchers found that, by the students’ second year of college, prevalence of opioid use increased by 85.7%, tranquilizers by 102.9%, and sedatives by 318.5%. Additionally, McLarnon and colleagues (2014) examined the nonprescribed use of sedatives and stimulants in participants ranging from age 18 to 48 years (all of whom had completed a postsecondary degree or were current students). Importantly, they found that both age of first use and age of peak use occurred during the ages of the traditional college student; the mean age of first use for sedatives was 20.5 and for stimulants was 17.8, and the age of peak use was 22.4 for sedatives and 19.3 for stimulants.

PDM Among Honors Students

Although a significant amount of research has examined PDM among college students, students affiliated with honors programs (or honors students) are a particularly understudied population within higher education. Honors students are academically gifted (meaning they “exhibit superior performance relative to peers” [Worrell et al., 2019]) and are enrolled in a special program or college within the university 1. Research on honors students indicates that they have more diverse and collaborative discussions with other students compared to nonhonors students, as well as more interactions with faculty, especially in their first year (Miller & Dumford, 2018). However, honors students are also often required to complete a thesis or additional academic work. They also tend to be higher in perfectionism than nonhonors students, which can lead to later stress and social disconnection (Rice et al., 2006).

These unique experiences could lead to differential rates of PDM in honors students, but for different reasons. Given the additional workload, it is possible that honors students face additional academic strain that could result in PDM. Agnew’s general strain theory explains deviant behavior through the presence of stress and strains on an individual; these strains lead to negative emotions (e.g., anger, despair, depression) that generate a delinquent response (Agnew, 1992). For example, results of one study indicated that those college students who felt more strain due to the COVID­19 pandemic were more likely to binge­watch television and online shop (Mowen & Heitkamp, 2022). Regarding PDM, higher amounts of strain in terms of not feeling safe or feelings of being treated unfairly at school led 7th through 12th grade students to be more likely to use 1Honors programs also typically have smaller class sizes with more individualized attention and often have special events (e.g., lectures, celebrations) for their program or college. (For a review of honors programs, their functions, and associated student outcomes, see Rinn & Plucker, 2019.)

alcohol, marijuana, and other illicit drugs (Peck et al., 2018). Thus, if honors students feel heightened stress due to any number of factors like increased academic demands, they may have different motivations than nonhonors students for engaging in PDM.

In contrast, the bonds formed by a smaller community may protect honors students against the risk of PDM. Hirschi’s social control theory makes the claim that people’s social bonds—attachment, commitment, involvement, and beliefs—diminish the likelihood of deviant behavior (Hirschi, 1969). Among a large nation­wide sample of adolescents (Ford, 2009) and a large sample of undergraduate students at a Midwestern university (Seredycz & Meyer, 2005), those who had stronger bonds with their parents and schools were less likely to misuse prescription drugs or other substances. Theoretically, a smaller, more personalized environment in conjunction could fulfill the components of the social bond theory by providing students with more opportunity for involvement and healthy attachment and contribute to lower levels of risky behavior such as PDM.

To our knowledge, only one study has specifically examined PDM in honors students. Pedalono and Frailing (2018) examined honors students enrolled at a small private religious university in the southern United States. The survey inquired about the strains of college life (e.g., time spent studying, time spent on extracurricular activities, expectations for success) and use of stimulants and pain killers without a prescription. The authors report that their results contradicted strain theory, as having lower expectations for success in school predicted higher stimulant use. The authors indicated this may be because about half of their sample were in their first year of college, adapting to a new environment, and may not have had many expectations for what their success in college should look like. It could also be that lower expectations actually result in more strain if students are forming their expectations around their current performance. Furthermore, this study looked at strain only in an honors student sample, which makes it difficult to draw conclusions regarding if honors students differ from those who are not affiliated with honors programs (i.e., nonhonors students) in their PDM, and if so, why that might be.

Present Research

The goal of the present study was to expand our understanding of the prevalence of and motivations for PDM in honors students as the literature is currently unclear if students affiliated with honors programs may be more or less likely than unaffiliated students to engage in PDM. Currently, there is little research on PDM among honors students in general, and the work that has been done

was not designed to examine whether honors program affiliation matters. Further, many studies have looked at only one type of prescription drug (most commonly, stimulants), were limited to a certain classification of student (e.g., first ­ year students in an introductory psychology course), or only looked at only one type of misuse (e.g., use without a prescription; see Young et al., 2021, for an exception). The present study collected data on four types of prescription drugs (i.e., stimulants, opioids, tranquilizers, and sedatives) and utilized a stratified random sampling procedure of students across majors and from all academic classifications, allowing for a more representative sample. In addition, it is important to investigate if honors and nonhonors students report different motives for PDM, such as academic or social strain motives, for future points of intervention. Our research questions were as follows: Among all students, how common is PDM and does that differ based on whether a student is enrolled in the honors college? Second, does PDM for each of the four drug classes differ among honor students and nonhonors students at two different time frames: in college and in the last two weeks? And finally, do the motives for general PDM differ between honors and nonhonors students?

Method

Participants, Procedure, and Design

This study was conducted at a large (> 20,000 students) public university in the southeastern United States. The Honors College program at the university started in 1997. Students are considered for admission to the Honors College based on grade point average (GPA), extracurricular involvement (including employment and community service), the level of rigor in high school courses, the strength of essays, and letters of recommendation. If selected, students are expected to complete 30 hours of courses with honors designations, achieve a minimum GPA of 3.50 by the time of graduation, and complete a capstone project (typically a written thesis). The Honors College has a designated building for student use, including classrooms, computer lab, and kitchen and lounge area.

The study was approved by the University of Mississippi Institutional Review Board and utilized an internet survey to collect data. A list of current undergraduates was supplied by the university registrar. A stratified random sample of each academic classification was drawn to ensure that the sample included more than first­year students. For each academic classification, we assumed a 5% margin of error and a 95% confidence level, and estimated a 15% response rate, resulting in invitation emails being sent to 1,785 first­year students, 1,725 sophomores, 1,745 juniors, and 1,775 seniors

(for a total of 7,030 emails). Potential participants were emailed an invitation to participate in a study being conducted by students enrolled in a survey research design course in the university’s Honors College and sponsored by the Vice Chancellor’s Office. The purpose of the study was to learn more about the student body and prescription drug use. Participants were informed that they were randomly selected, participation was voluntary, and that their responses were completely anonymous. Survey responses were recorded using Qualtrics, an online survey system.

Only participants who completed the entire survey (i.e., responded to some questions in all sections of the survey) were included in data analyses, resulting in a final sample of 558 with an overall response rate of 7.9% and a calculated margin of error of 4.08. One hundred thirty ­ five (24.2%) participants in the final sample

Note. Entries with - indicate no data available from the university.

TABLE 1

Demographic Information of the Sample and Campus Population

reported being students in the Honors College, which is a higher percentage than what we would expect to find in the student body given the size of the Honors College. A comparison of the demographics of the current sample compared to the demographics of the university can be found in Table 1. Our final sample consisted of about 76% nonhonors students, 71.1% women, 82.3% White, and a relatively equal distribution of first­years, sophomores, juniors, and seniors.

Measures

TABLE 2

Frequencies of PDM

Prescription Drug Misuse

Participants were asked about PDM separately for four prescription drug types: stimulants, opiates/pain medications, tranquilizers, and sedatives. For clarification, several examples of each drug type were provided in addition to the general categories of drugs (e.g., Stimulants: Adderall, Ritalin, Concerta, Vyvanse). For each drug type, participants were asked a yes or no question about consuming prescription drugs not prescribed to them and a yes or no question about using prescription drugs that were prescribed to them but taken in higher doses or more frequently than prescribed. For each behavior, they indicated whether they had engaged in this behavior across two different time frames: since coming to college and the preceding two weeks.

Motivations

For each of the four drug types, participants indicated whether they engaged in PDM for any of thirteen possible reasons/motives. The list of motives was compiled from motives examined in previous research studies that had examined PDM. Participants could endorse as many or as few motives as they wished. Motives asked about social (e.g., to have a good time at a party) and academic motivations (e.g., to improve my grades, to help me focus/concentrate), as well as other possible motivations/stressors (e.g., to lose weight, to get high). Students were asked about motives in general, and not at specific time periods. Finally, participants indicated their gender, race, academic classification, and whether they were a member of the honors college.

TABLE 3

Frequencies of PDM Motive Endorsement

Results

Regarding Research Question 1, the overall rate of PDM among the full sample of students, including all prescription drug types, was 35.84% (n = 200). A chisquare analysis found no difference between the number of honors (n = 42) and nonhonors (n = 158) students engaging in PDM, c2(1) = 1.73, p = .18, Cramer’s V = .05. Given that participants could report using multiple types of drugs, we summed the number of prescription drug types participants reported using in college (ranging from 1 to 4). Of the 200 participants who reported PDM, 74 reported using multiple types of drugs. An ANOVA found that honors students reported using significantly fewer drug types (M = 1.36, SD = 0.75) than nonhonors students (M = 1.72, SD = 1.00), F(1, 198) = 4.63, p = .03, Cohen’s d = 0.37).

The frequencies of PDM for each drug type for the overall sample can be found in Table 2. Consistent with previous research, stimulants were the most misused prescription drug since coming to college and in the preceding two weeks. For Research Question 2, we

conducted a series of chi­square tests that were used to compare PDM rates between honors and nonhonors college students in all four drug types and during both time frames (since coming to college and in the last two weeks). Chi­square analyses have been found to give robust estimates for unequal samples sizes, such as with the case of our honors and nonhonors student sample (Roscoe & Byars, 1971). However, because we had some cells across all chi­square analyses in which expected frequencies were less than five, we additionally calculated Fisher’s exact test which does not rely on this assumption. The p values from these tests were similar to those of the chi­square tests, so we have reported only the chi­square analyses for ease of interpretation.

Examination of PDM since coming to college revealed no significant differences between honors students and nonhonors students in stimulant use, tranquilizer use, sedative use, or opiate use. Similarly, examination of PDM in the preceding two weeks revealed no significant differences between the two student types in any of the four drug types.

For Research Question 3, a series of chi­square tests were used to determine whether the motives reported for prescription drug use differed between honors and nonhonors students in the sample of 200 participants who reported PDM (see Table 3). Regardless of classification, students were most likely to report PDM in order to help them focus and concentrate, improve their grades, and to help them stay awake. To simplify analyses regarding if honors and nonhonors students differed in their motivations, endorsements of the thirteen motives were collapsed across the four drug types. Of the thirteen motives, two significant differences emerged: nonhonors students were more likely than honors students to report engaging in PDM to improve their grades, c2(1) = 12.01, p < .001, Cramer’s V = .24, and to get high, c2 (1) = 4.22, p = .04, Cramer’s V = .15. The number of motives endorsed was compared using a one ­ way ANOVA. Though honors students did not differ from nonhonors students in their rates of PDM, honors students (M = 3.43, SD = 3.56) endorsed significantly fewer motives than nonhonors students for PDM (M = 4.85, SD = 3.66), F(1, 198) = 4.99, p = .03, Cohen’s d = 0.39.

Discussion

The primary aim of this research was to investigate rates and motives of PDM between honors and nonhonors college students. We found no significant difference in rates of overall PDM between honors students and nonhonors students in any of the four drug types. Given the lack of significant differences in the rates of PDM, this may suggest that honors students are no more or less at risk of engaging in PDM. Of course, caution should always

be exercised when interpreting null results. An optimistic view of these findings may lead to the conclusion that honors students appear to be no more susceptible to PDM than nonhonors students despite possible strain from their more challenging academic requirements and despite what general strain theory would suggest (Agnew, 1992). A more pessimistic conclusion may hold that honors students are no more protected from PDM than nonhonors students, despite more personalized attention and community­building programming, as social control theory (Hirschi, 1969) might predict.

Analysis of motivations for using prescription drugs did find that honors students were less likely than nonhonors students to report using to improve their grades or get high, but there were no differences reported in the other eleven motivations. In addition, honors students reported fewer motives for their PDM than nonhonors students. An open question remains as to why honors students are motivated to engage in this behavior given that they engage in it at similar rates as nonhonors students.

The results of the current study may point to honors college students being more varied than is generally considered to be the case. In their review of the state of the literature on gifted youth, Neihart (1999) noted that there has been on­going debate as to whether to view this population as being especially at­risk for psychological problems, due to perceived social and emotional deficits and alienation from peers, or being especially resilient, due to greater intelligence and cognitive capabilities. Neihart asserted that neither conclusion can be drawn and that there are more factors to be considered beyond whether one is gifted or not. In a subsequent review, Jones (2013) concluded that although gifted children and adolescents scored higher on some indices of psychological well­being, such effects were small and there was substantial variability in the studies reviewed.

Examining honors college students specifically, Cross et al. (2018) found that honors college students are not a uniform, unvarying type of student. In fact, they identified five unique profiles of honors students and found that these profiles of students differed in terms of perfectionism and suicide ideation. Rinn et al. (2020) found four different profiles of high ability students, and importantly there were some differences between these profiles in the likelihood of participating in honors programming. Thus, the null results of the current study in terms of PDM may be obscuring significant differences that exist between types of honors college students, with some being especially at risk and others being more resilient.

Future Directions and Limitations

Despite several strengths (large sample, stratified sampling methodology), there are several ways the Smith,

current work could be strengthened going forward. First, our sample was also fairly homogenous as it consisted primarily of students who identified as female and white. We recommend against generalizing results to other populations, such as students of color or students in other regions of the United States. As such, we would recommend that future research replicate these findings with a more diverse sample at different campuses in different regions of the country. Our study and the only other study examining PDM in honors students (Pedalono & Frailing, 2018) were both conducted in the southern United States. Research suggests that there are geographic differences in PDM (National Institute on Drug Abuse, 2020). In addition, these data were collected from a large public university which is frequently cited as a “party school” (according to one article, the university ranks in the top 25 party schools in the U.S.; Fish, 2021) with a strong fraternity and sorority presence (the university ranks in the top 15 U.S. universities for percentage of students engaged in Greek life; U.S. News Weekly, 2022). These groups have previously shown an association with increased PDM (Witcraft et al., 2019). Research has shown that students are more likely to engage in PDM to the extent that they believe that their friends engage in PDM (Young et al., 2021). It may be the case that honors programs differ from one another in the social norms surrounding PDM that are created among their students.

Future research should also directly examine aspects of the honors college experience that vary by campus (e.g., size, programming types, academic requirements). For example, the present sample was drawn from a university with an honors college that has its own building, advising, restricted course offerings, and even recognizable and frequently worn merchandise. As such, honors students at schools with a smaller program or different requirements may report differential rates of or motivations for PDM. As Miller and Dumford (2018) noted, there is a substantial degree of variability between honors colleges across the country. Further, honors students in the current sample, as is the case with many other honors programs, opted into this honors program. As such, a fuller understanding of the role of honors programs and their ability to promote beneficial outcomes and decrease problematic behaviors, like PDM, in high ability students will come from investigating those who are involved in honors programs (e.g., choose to apply, are accepted) and those who are not, a recommendation made by other authors (e.g., Rinn & Plucker, 2019).

In addition, the current study found that honor students reported fewer motives for engaging in PDM, though they showed equal prevalence to nonhonors

students. Although other research has examined PDM motives (e.g., Rabiner et al., 2009; Teter et al., 2006), future research should continue to examine motives for PDM and consider whether motives differ between student groups. For example, Rabiner and colleagues (2009) reported whether usage rates differed by fraternity/sorority membership but did not report whether there were differences in motivations. Teter et al. (2006) found differences and similarities in motives between male and female students but did not consider student organizations. Future researchers could investigate whether various groups on campus might have different motives for PDM, as this would help university administrators to target prevention efforts accordingly.

The current research did not consider individual difference variables such as major, socioeconomic status, housing type (e.g., on­campus or off­campus), peer support, ability to cope with adversity, social desirability, or personality traits as predictors of PDM. Considering that honors students are a heterogenous group, these variables should be considered in future work. Given that Cross et al. (2018) and Rinn et al. (2020) found personality differences even between honors and high ability students, additional research is needed that examines whether individual differences reliably predict differences between honors and nonhonors students in PDM. Consideration of individual differences may help elucidate whether PDM rates among high ability and honors students truly do not differ from typical ability students or whether the current null findings are a result of these unmeasured moderators. Notably, PDM is a sensitive topic and results may therefore be subject to bias. Future work should consequently consider measuring and controlling for social desirability.

The current study also did not use a validated measure of PDM motivation and we cannot say that our list of motives is exhaustive, or that the groupings are reliable. The results suggest that honors students and nonhonors students do not differ in their motivations for PDM. However, it is possible that they do, but we failed to find that difference because we did not assess those motivations. For example, in their examination of PDM in a nationwide sample of college students, Teter at al. (2006) found that 4.5% of participants reported misusing prescription drugs because “it is safe than street drugs,” which we did not assess. We encourage future researchers to continue to study PDM motives and work towards creating a psychometrically sound measure. In addition, researchers could examine motives qualitatively to better capture students’ motives for PDM beyond those that have previously been considered.

As a final suggestion, and one that is consistent with the observations of other scholars (e.g., Cross

et al., 2018; Miller & Dumford, 2018), more research examining honors college students is needed. There is very limited research conducted on honors students, including research on how student involvement in honors programs predict academic success, belongingness, well­being, and of course, PDM (e.g., Miller & Dumford, 2018; Rinn & Plucker, 2019). For high ability students, their academic achievement and things related to it may serve as both a way to cope with some stressors, but also a source of stress on its own, and this may change over time (Krafchek & Kronborg, 2019).

Implications for Practitioners

Results from the current study suggest that honors students may more closely resemble their nonhonors classmates than is generally assumed, at least in terms of engaging in PDM. By contrast, there are differences between honors and nonhonors students in terms of motivation for PDM. This paints a complicated picture for professionals working with college students. PDM prevention programs directed at the broader student body may still be beneficial. However, in one­on­one contexts, a more nuanced approach may be necessary. Assuming that students are engaging in PDM for the most common reasons––getting high or enhancing academic performance––may not accurately reflect the motives of clients who are honors students. This variability between students has been observed in other studies; Peck et al. (2018) found that White, Black, and Hispanic adolescents differed in their motives for substance use.

Higher education professionals, like many people, may have preconceived notions of honors college students of either being especially at­risk for psychological problems or being especially resilient in the face of college stressors due to assumptions about the implications of giftedness (Jones, 2013; Neihart, 1999). Relying on this either/or thinking may have negative consequences for honors students seeking support. It may be the case that potential problems are not noted because these students are assumed to be somewhat immune to the common stressors or temptations of the average college student. It could also be the case that these students are assumed to be struggling with particular problems (e.g., problems relating to other students, isolation) when the issues causing distress are unrelated to their designation as a highly achieving student (e.g., financial concerns). The similarity between honors students and nonhonors students in the current study in their PDM use suggests that practitioners working with college students should consider their potential biases pertaining to different types of students.

As for student life professionals who work directly with honors programs, continued implementation of programs that help students to bond with one another,

Smith, Haupt, and Jordan | Prescription Drug Misuse and Honors

the honors college, and the university seems warranted, as past research does indicate that for adolescents, social bonds with parents and schools leads to less PDM (Ford, 2008). However, research does suggest that social norms or believing that one’s friends are engaging in PDM are also associated with increased PDM (Young et al., 2021). Honors programs should monitor and research whether these programs are effective at enhancing social bonds, reducing stress, and if they are associated with more or less PDM. Research on the efficacy of these programs could be used to bolster student life within other areas of the university as well.

Conclusion

College students are particularly susceptible to PDM (Benson, et al., 2015). The present study adds to the understanding of young people’s misuse of prescription drugs and the experience of honors students. Using stratified random sampling, the results of the current study found no significant difference between rates of PDM among honors and nonhonors students but did find that honors students were less likely to report engaging in PDM for grade maintenance and to get high. It is our hope that this research will be of interest to those who work in honors programs at the college level.

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Author Note

C. Veronica Smith https://orcid.org/0000­0002­9123­0244

Lauren N. Jordan https://orcid.org/0000­0002­7628­7058

Lauren N. Jordan is now at the Department of Psychology at Coastal Carolina University, Conway, South Carolina.

This article is adapted from the undergraduate honors thesis completed by Haupt in 2020.

Data are available at https://researchbox.org/688. The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article. The authors received no financial support for the research, authorship, and/or publication of this article.

Correspondence concerning this article should be addressed to C. Veronica Smith, Department of Psychology, University of Mississippi, P.O. Box 1848, University, MS 38677, United States. Phone: 662.915.1075. Email: csmith4@olemiss.edu

Physiological Implications of Exclusion in Individuals With ADHD Symptomatology

Jaz E. Curtis, Sierra S. Swenson, Mariel Olsem, Annaka Scherf, and Rebecca J. Gilbertson*

Department of Psychology, University of Minnesota Duluth

ABSTRACT. Attention­deficit/hyperactivity disorder (ADHD) is a neurodevelopmental disorder characterized by inattention, hyperactivity, and impulsivity. Rejection sensitivity, the tendency to anxiously expect, perceive, or intensely react to social rejection, is notably prevalent in those with ADHD. We investigated the physiological responses of individuals with ADHD symptomatology during a social exclusion task. Participants (N = 60, ages 18–38; 26.7% men, 73.3% women) self­reported ADHD symptoms and completed a Go/No­Go task to objectively assess attention and impulsivity. In this task, participants responded to “Go” stimuli (attention) and withheld responses to “No­Go” stimuli (impulsivity). Social exclusion was manipulated using the Cyberball task, during which heart rate (BPM) was measured via electrocardiogram (ECG). To indirectly measure rejection sensitivity, social threat perception was assessed using the Need­Threat Scale (NTS) posttask. Contrary to previous literature, BPM decreased during the task and increased posttask, F (2, 114) = 13.30, p < .001, η ² = .19, with no group differences in physiological responses during or after exclusion. Further, we found a negative association between NTS total scores (with scale indication) and ADHD symptoms, r(57) = ­.44, p < .001, indicating lower basic need (higher perceived social threat) in those with more reported ADHD symptoms. These findings indicate heightened rejection sensitivity in individuals with ADHD symptoms but no corresponding physiological differences. Future research could explore stronger social exclusion manipulations and direct measures of rejection sensitivity to better understand these associations.

Keywords: ADHD, physiological response, social exclusion, rejection sensitivity, ECG

Attention­deficit/hyperactivity disorder (ADHD) is a neurodevelopmental condition marked by patterns of inattention, hyperactivity, and impulsivity, which can severely impact daily functioning and overall quality of life (National Institute of Mental Health, 2023). It is one of the most common childhood­onset psychiatric disorders, with a worldwide

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prevalence estimated to be around 5% in children and adolescents. ADHD often persists into adulthood, with approximately 60% of children diagnosed with ADHD continuing to experience symptoms (Faraone et al., 2021). ADHD is a complex disorder with a multifactorial etiology involving genetic, environmental, and neurobiological factors. Family, twin, and adoption

Physiological Implications of Exclusion

ADHD | Curtis, Swenson, Olsem, Scherf, and Gilbertson

studies have shown that ADHD has a strong genetic component, with heritability estimates ranging from 70% to 90% (Faraone & Larsson, 2019). Environmental factors such as prenatal exposure to nicotine, alcohol, or maternal stress have also been implicated in the development of ADHD (Zeeuw et al., 2012). ADHD is more commonly diagnosed in men than women, with a male­to­female ratio ranging from 3:1 to 9:1, depending on the diagnostic criteria used, due to differences in symptom presentation and the presence of comorbid conditions (Skogli et al., 2013).

Rejection Sensitive Dysphoria

Research has focused on the cognitive and behavioral symptoms of ADHD. For example, impulsivity has been demonstrated using a Go/No­Go task (Bezdjian et al., 2009). However, emotional symptoms of ADHD, particularly in relation to threat perception, are just as prevalent in ADHD. Rejection sensitive dysphoria is the feeling of emotional pain due to a failure or rejection. It is estimated to affect many individuals with ADHD, who experience greater sensitivity to rejection than those without ADHD (Bedrossian, 2021). An example of rejection sensitive dysphoria would be an increase in emotional pain experienced from a perceived failure to meet self or others’ expectations. Rejection sensitive dysphoria symptoms can include anxiety, low selfesteem, and emotional outbursts following perceived rejection. Although rejection sensitive dysphoria is not recognized in the DSM ­ 5, it is thought to be related to decrements in neural activity involving brain areas responsible for attention, emotion regulation, behavior, and arousal (Bedrossian, 2021). In this study, we explored the concept of rejection sensitivity as a specific form of threat perception, with a focus on social threats. As an indirect measure of rejection sensitivity, we utilized a scale that measures various aspects of threat perception, including those related to social rejection.

Physiological Arousal

Physiological arousal includes a range of bodily responses that reflect the activation of the autonomic nervous system in response to internal and external stimuli (Buchanan & Tranel, 2008; Purves et al., 2001). One of the key indicators of physiological arousal is the modulation of heart rate and blood pressure. Heart rate increases with heightened arousal, reflecting the body’s preparation for action or response to a stimulus. Similarly, blood pressure, the force exerted by the blood against the walls of the arteries, also tends to rise in response to increased arousal (Azarbarzin et al., 2014). These physiological changes are part of the body’s adaptive response to stress, excitement, or other stimuli,

and measurement can provide valuable insights into an individual’s emotional and cognitive processes. Elevated levels of arousal have been linked to increased attention, vigilance, and readiness to respond to environmental demands (Oken et al., 2006).

Physiological Arousal During Social Exclusion

Sijtsema et al. (2011) investigated physiological arousal during social exclusion. They found that girls displayed increased physiological reactivity during a social exclusion task. Baseline physiological activity (heart rate, respiratory sinus arrhythmia, and skin conductance) was assessed before, during, and after the exclusion Cyberball task (Williams et al., 2000). After the task, the Children’s Rejection Sensitivity Questionnaire was used to assess the participants’ sensitivity to rejection. Similarly, Iffland and colleagues (2014) also employed the Cyberball task (Williams et al., 2000) to investigate the effects of social exclusion on physiological responses in neurotypical young adults. Participants were randomly assigned to either a social exclusion or inclusion condition of the task. The researchers recorded participants’ physiological responses, including skin conductance level and heart rate. They found that participants in the social exclusion condition had an increased heart rate during the task, suggesting that social exclusion can lead to increased physiological arousal.

Psychological Arousal During Social Exclusion in ADHD

Research on social exclusion and psychological responses in individuals with ADHD remains limited. A study by Babinski et al. (2019) has shown that individuals with ADHD may exhibit heightened neurophysiological reactivity to rejection and higher levels of self­reported rejection sensitivity during social exclusion. In their study, a sample of 609 children aged 3 to 6 years old participated, with their mothers providing self­reported ADHD data. The children completed the Island Getaway task (Kujawa et al., 2014) and a self­report measure of rejection sensitivity, while electroencephalogram (EEG) data was recorded. In this task, participants were told they would be playing a game with 11 age­matched coplayers in which they would travel to the Hawaiian Islands. At each island, they had to vote on whether they wanted each coplayer to continue in the game and received feedback on how coplayers voted for them. The study found that higher ADHD symptom severity was associated with an enhanced EEG neural response to rejection and greater self­reported rejection sensitivity. This suggests a change in brain activity that is sensitive to social rejection. These studies highlight the complex interplay between rejection sensitivity and physiological responses to social exclusion. More research is needed

Curtis, Swenson, Olsem, Scherf, and Gilbertson |

to understand the physiological relationship between ADHD and social threat perception.

The Present Study

This study aims to investigate the physiological relationship between ADHD and social exclusion by examining the connection between ADHD, selfreported social threat perception, and physiological responses, as measured by heart rate and blood pressure. Given the previous literature, the current study sought to enroll adults of all genders who were either neurotypical or had ADHD symptoms or a diagnosis. Similar to Iffland and colleagues (2014), we used the Cyberball task (Williams et al., 2000), a validated paradigm used to manipulate feelings of social exclusion. Rejection sensitivity was operationally defined and measured through threat perception (as a manipulation check) using the Need­Threat Scale (Williams et al., 2000). To measure physiological responses to social exclusion, ECG recordings were used to monitor participants’ heart rate, measured as beats per minute (BPM), continuously throughout the baseline recording, during the Cyberball task, and posttask recording. Blood pressure was measured using an automated Oscillo metric blood pressure cuff at specific time points: baseline (before the Cyberball task), immediately after the exclusion phase, and during posttask period. These measurements provided both dynamic and static physiological indicators of participants’ responses to social exclusion. We had three main hypotheses. We first hypothesized that participants with ADHD would demonstrate more impulsive choices on the Go/No­Go task (Fillmore et al., 2005) as compared to neurotypical individuals. The Go/No­Go task was included as a behavioral measure of impulsivity that reliability shows differences between individuals with ADHD versus neurotypical individuals (Bezdjian et al., 2009). As formal clinical diagnosis of ADHD was not a part of the study, the Go/No­Go task was used to validate the self ­ reported ADHD symptom checklist. Second, due to heightened rejection sensitivity, individuals with ADHD symptoms would have an increase in heart rate and blood pressure during and after the Cyberball exclusion task as compared to individuals with no ADHD symptoms. Finally, there would be a difference in social threat perception after completing the Cyberball task between individuals with ADHD symptoms and neurotypical individuals, those with ADHD symptoms perceiving higher social threat. Previous literature is constrained by inclusion of either males or females and/or lack of a control group (neurotypical). Thus, the current study extends previous literature by including all genders and comparison of rejection sensitivity and physiological measures in

individuals with ADHD symptoms as compared to neurotypical individuals.

Method

Participants

Prior to data collection, approval from the Institutional Review Board at the University of Minnesota Duluth, a comprehensive university in the Midwest, was obtained. The university students were notified of the experiment and recruited via an online participant database (SONA Systems). Eligible participants were at least 18 years of age with between 11 and 17 years of education and had the proficient ability to read and speak English. After voluntarily signing up for a lab session, participants were screened for factors such as age, medical history (including heart history), and any pre­existing conditions that could potentially impact performance on pen­andpaper, heart rate, or computerized tasks (e.g., a diagnosis of Parkinson’s, dementia, epilepsy, restless leg syndrome, uncorrected vision, cardiac arrest, high blood pressure, or other related health conditions). Due to sample pool constraints, participants were not specifically screened for ADHD but later assessed for ADHD symptoms. Of the 60 participants in the current sample, 73.3% were female and 26.7% were male assigned at birth. Due to the university’s population, participants were primarily European American (90%). Other ethnicities that were represented were Asian (1.7%), African American (1.7%), and multiple ethnicities (6.7%). The average age of participants was 19.58 years (SD = 2.89, range = 18–38). All 60 screened participants were eligible and were directly enrolled into the study. Participants either received course

Note. The Cyberball task (Williams et al., 2000), a paradigm used to simulate social exclusion in research settings. Three cartoon players are shown tossing a ball to each other. Player 1 and Player 3 are computergenerated and are programmed to include or exclude the participant (Player 2) during the game.

FIGURE 1

Cyberball Task Illustration

credit or a $15 Visa gift card for completing the study. The informed consent form provided information about the purpose and potential risks of the study. Prior to participation, participants provided written consent and were debriefed immediately following the laboratory session.

Measures and Materials

Cyberball Task

Exclusion was manipulated using the Cyberball task (Williams et al., 2000), a computerized paradigm simulating a ball ­ tossing game, administered via Millisecond software (Inquisit 6 [Computer software], 2022b). This is a cartoon video game ­ like task (see Figure 1) where the participant and computer­generated players play a game of catch. The task has two conditions: inclusion or exclusion. The inclusion condition throws the ball to the participant every time, whereas the exclusion condition never throws the ball the participant. This task was specifically coded for this study to add a partial inclusion condition where participants would get thrown the ball at first but then after a few throws they would be excluded for the rest of the task. The custom schedule throw code is available from the first author.

Heart

Rate Variability and Blood Pressure

Throughout the study heart rate was measured continuously with an ECG (MP150; Biopac Systems) to assess differences in physiological arousal. Electrodes were placed under the left and right clavicle and under the left rib cage. Data was processed offline using AcqKnowledge software, capturing heart rate in BPM. Additionally, blood pressure was monitored with a 3 Series Upper Arm Blood Pressure Monitor. This cuff was secured above the elbow of participants’ dominant arm. Blood pressure measurements were taken at 5 points throughout the experiment. These included twice during

baseline, after the Go/No­Go task, after the Cyberball task, and following the 5­min posttask period. Blood pressure was assessed in terms of systolic blood pressure and diastolic pressure.

Go/No-Go Task

For an objective measure of ADHD behavior, inhibitory control and response inhibition were assessed using a computerized Go/No­Go task (Fillmore et al., 2005). The task was presented on a desktop computer using Millisecond software (Inquisit 6 [Computer software], 2022a). Participants were given detailed instructions explaining the nature of the task. The task lasted 15 minutes and consisted of a series of visual stimuli presented on the computer screen. The “Go” stimulus (a green rectangle) occurred with high frequency, and the “No­Go” stimulus (a blue rectangle) occurred infrequently. The order of stimulus presentation was randomized to prevent predictability. Participants responded to frequent “Go” stimuli to access attention and withheld responses to infrequent “No­Go” stimuli to access impulsivity. Reaction time, accuracy, and false alarm rates were recorded.

Need-Threat Scale

To assess rejection sensitivity, we employed the NeedThreat Scale (NTS; Williams et al., 2000), α = .87. This scale was designed to measure the perception of various types of threats, encompassing physical, social, and psychological domains. Although the NTS does not directly measure rejection sensitivity, it captures the broader construct of threat perception, which includes the social threats central to rejection sensitivity. Thus, the NTS serves as an indirect measure of rejection sensitivity by evaluating participants’ perceived threats in social contexts. The NTS was used to measure participants’ subjective experiences of threat to fundamental psychological needs after the Cyberball task (Williams et al., 2000) induced social exclusion. This

Note. Procedure timeline for the experimental tasks. The timeline includes the following steps: participants completed a demographic questionnaire, followed by an ECG baseline recording to establish physiological measures. The Go/No Go Task (Fillmore et al., 2005) was then administered to assess response inhibition, followed by the Cyberball task (Williams et al., 2000) to simulate social exclusion. Afterward, an ECG posttask recording was conducted. Participants then completed the Need-Threat Scale (Williams et al., 2000) to assess their experience during the Cyberball task, concluding with the ADHD Self-Report Screening Scale (Kessler et al., 2005) to measure ADHD symptoms.

FIGURE 2 Procedure Timeline

Swenson, Olsem, Scherf, and Gilbertson | Physiological

measure consisted of 20 items, with each factor having 5 items, and used a rating scale ranging from 1 (not at all) to 5 (extremely). The four basic need competency subscales include belonging (“I felt I belonged to the group”;  α = .58), control (“I felt I had control over the course of the game”;  α = .42), self­esteem (“I felt good about myself”;  α = .62), and meaningful existence (“I felt important”; α = .68). Higher scores indicated higher levels of basic need competency and lower social threat perception (Williams et al., 2000). Conversely, low scores (as shown in participants with ADHD symptoms in the current study) show higher social threat perception.

Adult ADHD Self-Report Screening Scale

To measure symptoms of ADHD, participants completed the Adult ADHD Self­Report Screening Scale (ASRS; Kessler et al., 2005), α = .91. This scale assesses selfreported adult ADHD symptoms, providing information about attention and hyperactivity. The ASRS consists of Part A (6 items) and Part B (12 items). Part A contains items that are most predictive of ADHD, and Part B provides additional information on symptom severity and the impact of inattention or hyperactivity. Example items include “How often do you have trouble wrapping up the final details of a project, once the challenging parts have been done?” and “How often do you feel overly active and compelled to do things, like you were driven by a motor?” Participants rated each item on a scale ranging from 1 (never ) to 5 ( very often ). If a participant scored 4 or more in Part A, their symptom profile is highly consistent with an ADHD diagnosis in

Prior to participation, individuals were screened for eligibility based on factors such as age, medical history, and any pre­existing conditions that could potentially impact performance on pen­and­paper, physiological, or computerized tasks. Upon meeting eligibility criteria, participants were invited to continue the laboratory session (for procedure timeline, see Figure 2). After the consenting process, participants were instructed how to put on the ECG electrodes and then were connected to a monitoring system (Biopac, Inc). Researchers were trained by the principal investigator with personal communication with Biopac, Inc. and with Buchanan (Buchanan & Tranel, 2008) and utilized the Neurocognitive Laboratory Training Manual. The researchers demonstrated the correct placement of the electrodes to the participants and ensured they were properly applied. The principal investigator monitored all results. Participants with incomplete physiological or demographic data (n = 7, 11.67%), were removed from the study. Once the electrodes were in place and the equipment was connected correctly, participants rested for 10 minutes to allow the electrodes and conductive gel to produce accurate recordings. During this time, participants completed the Go/No­Go task (Fillmore et al., 2005). Then a baseline ECG recording was then obtained over a period of 5 minutes while participants Curtis,

adults (Adler et al., 2006; Kessler et al., 2005). In this study, participants were designated in the ADHD group if they scored a 4 or more on Part A.

Procedure

Note. Correlation matrix of the Adult ADHD Self-Report Scale (ASRS; Kessler et al., 2007) total scores with the Need-Threat Scale (NTS; Williams et al., 2000) subscales and total scores, Go/No-Go task (Fillmore et al., 2005) total errors, heart rate (BPM) before, during, and after the exclusion task, blood pressure (BP) before and after the exclusion task. Differences in n is indicative of missing data. **Correlation is significant at the .01 level (2-tailed). * Correlation is significant at the .05 level (2-tailed)

TABLE 1

Physiological Implications of Exclusion in ADHD | Curtis, Swenson, Olsem, Scherf, and Gilbertson

were at rest. During ECG recording, participants then engaged in the Cyberball task (Williams et al., 2000). Participants were instructed that they would be playing a virtual ball­tossing game with two other participants, who were located in different rooms. Initially, all participants received the ball regularly during a brief inclusion phase. This phase lasted for approximately 1 minute, and each participant experienced fair and equal ball tosses between themselves and the two virtual players. Then, participants entered the exclusion phase, during which they were excluded from receiving the ball for 5 minutes to induce feelings of social exclusion. Following the exclusion task, participants underwent an additional 5­minute ECG posttask measurement. Then participants were asked to rate their feelings of social exclusion, emotional distress, and overall mood using the NTS (Williams et al., 2000). Then participants completed the ASRS (Kessler et al., 2005). The order of the tasks was not counterbalanced due to pre­ and posttask physiological measures and inclusion of NTS after the exclusion task. All participants were debriefed at the end of the study and provided with relevant contact information for any inquiries or concerns. To ensure participant confidentiality and data protection, all procedures followed the university’s security standards. Electronic data was stored on a password­protected computer, and all paper records, including consent forms and demographic information, were kept in a locked file cabinet within a secure office. Only authorized research personnel had access to the data, and all identifying information was separated from research data.

Statistical Analyses

All statistical analyses were conducted using IBM SPSS Statistics (Version 29). Descriptive statistics were calculated for all variables (See Table 1). To analyze if participants with ADHD demonstrated more impulsive choices on the Go/No­Go task (Fillmore et al., 2005) as compared to neurotypical individuals, independentsamples t tests were conducted. To examine the effects of social exclusion on physiological responses, a repeated measures analysis of variance (ANOVA) was conducted with ADHD and the control group as the between­subjects factor and time (baseline, during task, and posttask) as the within­subjects factor. To assess if individuals with ADHD symptoms had increased heart rate and blood pressure during and after the Cyberball task (Williams et al., 2000), independent­samples t tests were conducted. Statistical significance was set at p < .05 for all analyses. Pearson correlation coefficients were used to analyze if threat perception (NTS; Williams et al., 2000) differed after completing the Cyberball task between individuals with ADHD symptoms and neurotypical individuals.

Results

ADHD Measures

Participant ADHD symptoms were assessed using the ASRS (Kessler et al., 2005). Of the total sample, 61.7% screened positive for ADHD symptoms (a score of a 4 or more on the ASRS). Among these individuals, 21.7% had a current ADHD diagnosis, and 18.3% were currently taking ADHD medication. We hypothesized that participants with ADHD would demonstrate more impulsive choices on the Go/ No ­ Go task (Fillmore et al., 2005) as compared to neurotypical individuals. Individuals who had a self-reported ADHD diagnosis ( n =13) had greater impulsivity errors (i.e., responding on the no­go cue; M = 2.67, SD = 4.18), as compared to participants without ADHD diagnosis (M = 1.48, SD = 1.85). However, an independent­samples t test indicated that this difference was not statistically significant, t(56) = 1.73, p = .08. Individuals who scored positive for ADHD symptoms on the ASRS (M = 1.74, SD = 2.73) did not have more impulsivity errors compared to the control participants ( M = 1.70, SD = 2.20). An independent ­ samples t test also confirmed that this difference was also not statistically significant, t(56) = 0.07, p = .95.

Physiological Measures

Physiological responses were monitored using ECG technology. We hypothesized that individuals with ADHD symptoms would have an increased heart rate and blood pressure during and after the Cyberball exclusion task as compared to controls. As data was collected for neurotypical and ADHD participants across the baseline, Cyberball task, and posttask time points of the laboratory session, a repeated measures ANOVA was employed to assess this hypothesis (see Figure 2). ANOVA findings showed there was a significant time effect across ECG measures where BPM decreased from baseline during the task and increased during the posttask measure, F(2, 114) =13.30, p < .001. Post hoc analyses showed a significant decrease in BPM from baseline (M = 84.08, SD = 1.68), to during the task (M = 80.19, SD = 1.58), followed by a significant increase during the posttask measure (M = 83.55, SD = 1.47), all ps < .001. The group and Group x Time interactions did not differ significantly, ADHD versus neurotypical participants n.s., p > .05 in each analysis. This suggests that physiological responses during social exclusion may not be associated with ADHD symptomatology. Blood pressure significantly decreased during the laboratory session, F(4, 224) = 14.13, p < .001. Post hoc tests showed that blood pressure at baseline was significantly higher as compared to posttask measure, p < .001.

Curtis, Swenson, Olsem, Scherf, and Gilbertson | Physiological

Threat Perception

Threat perception was assessed using the NTS (Williams et al., 2000) and we hypothesized that there would be a difference in social threat perception after completing the Cyberball task between individuals with ADHD symptoms and controls. A negative correlation was found between total scores and ADHD symptoms, r(57) = ­.44, p < .001, indicating that higher ADHD symptoms were associated with lower levels of basic need competency. Suggesting a high social threat perception during social exclusion. As higher scores on the NTS measure indicate greater emotional control, individuals that scored greater on the ADHD scale scored for lower emotional control. This correlation was found in each subscale (i.e., greater ADHD symptoms correlated with lower reported self­esteem, belonging, control, and meaningful existence; see Table 1). Although the sample was recruited as a convenience sample, 61.7% of participants screened positive for ADHD symptoms’, thus, given the small n of neurotypical individuals, the correlation analysis was conducted with all participants included. Demonstrated in the current study by the finding that individuals with ADHD had greater social threat perception as measured after the Cyberball task, suggest that individuals with higher ADHD symptoms or an ADHD diagnosis may exhibit distinct emotional responses following social exclusion.

Discussion

The purpose of this study was to investigate the physiological and emotional responses of individuals with ADHD symptomatology during a social exclusion task. We found that individuals with ADHD symptoms experience greater social threat perception but show no physiological differences during social exclusion. Participants completed self­reported measures of ADHD symptomatology and underwent objective assessments of ADHD behavior using the Go/No­task (Fillmore et al., 2005). Physiological responses were monitored using ECG technology and blood pressure. The Cyberball task (Williams et al., 2000) was used to manipulate social exclusion, and participants’ heart rate and blood pressure were measured before, during, and after the task. Selfreported measures of threat perception were assessed using the NTS (Williams et al., 2000) after the task. The study aimed to examine how individuals with ADHD symptomatology differ in their physiological arousal and threat perception in response to social exclusion as compared to those without ADHD symptoms.

Concerning the findings related to ECG and the Cyberball task (Williams et al., 2000) the significant decrease in BPM from baseline to during the task, followed by an increase during the posttask measure

is contrary to previous literature. For example, Backs and Seljos (1994) found an increase in heart rate during cognitive tasks. Similarly, in a study that included the Cyberball task, Iffland and colleagues found a decrease in BPM in the inclusion group and no BPM changes in the exclusion group. Differences between the current study and published literature could be due to the strength of manipulation of the Cyberball task. For example, it is possible that the task did not induce the anticipated level of social exclusion that has typically been seen in studies utilizing this paradigm. The significant overall decrease in blood pressure observed during the laboratory session suggests a potential calming or adaptive physiological response over the course of the session (see Muthard & Gilbertson, 2016). Our findings are inconsistent with what we typically find in other studies of stress system response when recording physiological data. Post hoc tests revealed that blood pressure at baseline was significantly higher compared to the posttask measure, indicating that participants experienced a reduction in blood pressure after engaging in the task. Interestingly, there were no significant differences between in the group and Group x Time interactions regarding blood pressure, implying that the observed physiological changes are not specifically associated with ADHD symptomatology but rather a generalized response to the task. Further research utilizing stronger manipulations of social exclusion is needed to better investigate the relationship between ADHD symptomatology, social threat perception, and physiological responses.

The finding of a significant negative correlation between NTS (Williams et al., 2000) total scores and ADHD symptoms, indicated that greater ADHD symptoms were associated with lower basic need competency (i.e., higher threat perception) after the exclusion task. This negative correlation was consistent across all NTS subscales, including selfesteem, belonging, control, and meaningful existence. These results align with broader theoretical frameworks, such as Barkley’s (1997) theory of ADHD as a disorder of self­regulation, that deficits in self­regulatory processes may contribute to heightened emotional reactivity and sensitivity to social stressors. Heightened threat perception may reflect underlying difficulties with modulating emotional responses, which are central to ADHD symptomatology. These results suggest that individuals with higher ADHD symptoms may exhibit distinct emotional responses following social exclusion. The observed association between higher ADHD symptoms and increased rejection sensitivity aligns with previous research indicating that individuals with ADHD may be more susceptible to experiencing rejection and in negative social interactions (Carpenter

Physiological Implications of Exclusion in ADHD | Curtis, Swenson, Olsem, Scherf, and Gilbertson

Rich et al., 2009). This susceptibility could stem from deficits in executive functioning and emotional regulation, which impair the ability to interpret and respond adaptively to social cues. These impairments may create a cycle of heightened rejection sensitivity, leading to greater social withdrawal or maladaptive behaviors that further strain interpersonal relationships. The heightened overall rejection sensitivity observed in individuals with higher ADHD symptoms may contribute to the difficulties in social functioning and interpersonal relationships that are commonly reported in this population. Findings highlight the importance of considering emotional responses, particularly rejection sensitivity, in understanding the social difficulties experienced by individuals with ADHD (Bedrossian, 2021). Further research is needed to understand the underlying mechanisms linking ADHD symptoms and emotional responses to social exclusion, which could inform interventions aimed at improving social functioning in this population.

There was a high percentage of participants who screened positive for ADHD symptomatology, with 61.7% of the sample meeting the criteria. This prevalence is considerably higher than the typically reported rates of ADHD in the general adult population, which range from approximately 2.5% to 4.4% (Simon et al., 2009), affecting the study’s generalizability. Advertising material included recruitment for individuals with and without ADHD. Thus, the sample was recruited as convenience, and it is possible that mention of ADHD in recruitment materials resulted in a higher rate of response by individuals who screened positive for ADHD symptoms. This sampling bias could limit the extent to which the results apply to the broader population, as the sample may not accurately reflect the general distribution of ADHD in the community.

There was a trend towards significance indicating that participants with self­reported ADHD diagnosis exhibited greater impulsivity errors compared to those without a diagnosis. However, individuals who scored positive for ADHD symptoms on the ASRS (Kessler et al., 2005) did not show a significant association with impulsivity errors. These results suggest a discrepancy between self­reported ADHD diagnoses, the self­reported ASRS symptom scale in our sample, and the effects on the impulsivity task (cued Go/No ­ Go). Importantly, the results of the current study are constrained to the methodology employed. Future studies could employ additional behavioral and self­report measures to provide a more comprehensive assessment of impulsivity. Tasks such as the Balloon Analogue Risk Task (Lejuez et al., 2002), which assesses risk­taking, the Barratt Impulsivity Scale (Patton et al.,

1995), which measures trait impulsivity, or the UPPS­P Impulsive Behavior Scale (Whiteside & Lynam, 2001), which evaluates multidimensional aspects of impulsivity, may help clarify the observed discrepancies and provide a better understanding of ADHD symptomology.

Limitations

While interpreting the findings of this study, several limitations should be considered. It is important to acknowledge that the sample in our study was not representative of the general population, which limits the generalizability of our findings. Our sample was predominantly women (73.3%) and White (90%), which does not reflect the gender and racial diversity of the broader population. The lack of diversity in the sample limits the extent to which these findings can be applied to more diverse populations. Efforts should be made to recruit a more ethnically and culturally diverse sample. Given predominance of European American participants, findings may not apply to other race/ ethnicities.

Given that ADHD is more commonly diagnosed in men than women (Skogli et al., 2013), the overrepresentation of women in our sample could have influenced the findings, particularly concerning the prevalence of ADHD symptomatology and impulsivity errors. Additionally, the sample size of participants with a self­reported ADHD diagnosis was relatively small (n = 13), which may have limited the statistical power to detect significant differences in impulsivity errors between the ADHD and non­ADHD groups. Future studies should include a larger sample size of individuals with a confirmed ADHD. To address this issue in future research, it would be beneficial to employ more rigorous recruitment methods that ensure a more balanced and representative sample of individuals with and without ADHD. For example, recruiting participants from diverse, general population ­ based samples or employing random sampling techniques could help ensure that the prevalence of ADHD in the sample more closely aligns with population­level estimates. Additionally, the use of self­reported measures of ADHD symptoms may be subject to response bias and may not fully capture the extent of ADHD. Future studies could benefit from using a combination of self­report measures and clinician­administered assessments to provide a more comprehensive evaluation of ADHD symptoms. Furthermore, the study’s reliance on a single task, the Go/No­Go task (Fillmore et al., 2005), to assess impulsivity may limit the generalizability of the findings. Including additional behavioral measures of impulsivity could provide a more comprehensive understanding of ADHD symptoms.

Curtis, Swenson, Olsem, Scherf, and Gilbertson | Physiological Implications of Exclusion in ADHD

Regarding the opposite physiological findings of Iffland et al. (2014) during the Cyberball task, the task strength of the social exclusion manipulation of the Cyberball task (Williams et al., 2000) could possibly be strengthened by including a greater number of trials and increasing task duration. Manipulation for social exclusion could be adjusted, for example the use of virtual reality. Additionally, due to rejection sensitivity being indirectly measured through the NTS (Williams et al., 2000), future studies might benefit from incorporating more direct measures of rejection sensitivity. Given the preliminary nature of these data, further studies are needed prior to including these findings into clinical applications.

Conclusion

These findings suggest that although individuals with ADHD symptoms may not show distinct physiological responses during exclusion, they may experience threat perception differently. The study’s findings contribute to the growing literature on the interplay between ADHD, physiological responses, and rejection sensitivity during social interactions. Despite the limitations, the observed negative correlation between ADHD symptoms and perceived threat adds to our understanding of emotional responses in individuals with ADHD. Future research should aim to address the generalizability, ADHD grouping, self­report, and task limitations by employing larger samples, including more individuals diagnosed with ADHD, and refining social exclusion paradigms to improve task manipulation and incorporate measures of direct perceived social rejection.

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| Curtis, Swenson, Olsem, Scherf, and Gilbertson

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Author Note

We have no known conflict of interest to disclose. This study was supported through an award provided by the Undergraduate Research Opportunity Program at the University of Minnesota Duluth. Equipment was provided by the Neurocognitive Laboratory at the University of Minnesota Duluth, led by Rebecca Gilbertson.

Correspondence concerning this article should be addressed to Jaz Curtis, Department of Psychology, University of Minnesota Duluth, 125 Bohannon Hall, 1207 Ordean Court, Duluth, MN 55812, United States. Email: jazecurtis@gmail.com

A Driving Simulator Experiment to Teach Experimental Design in an Undergraduate Psychology Research Methods Course

Forrest Toegel*, Mackenzie Baranski, and Cory Toegel* Department of Psychological Science, Northern Michigan University

ABSTRACT. In recent years, there has been increased interest in developing undergraduate research experiences that conduct novel scientific research during normal course time. The present study provided students in a psychology research methods course with a hands­on laboratory experience to study effects of alcohol intoxication goggles on behavioral measures related to driving. In the laboratory portion of class over 3 consecutive semesters, 83 students completed field sobriety tests and driving simulator trials under 4 visual impairment conditions: no goggles (–BAC), clear goggles (0.00 BAC), Fatal Vision White Label goggles (< 0.06 BAC), and Fatal Vision Black Label goggles (≥ 0.25 BAC). Students experienced 1 condition each week for 4 weeks, and then the initial condition was repeated on the 5th week to allow for an evaluation of common threats to internal validity. Condition order was counterbalanced across randomized groups of students. Students generally engaged in the experience at high rates, submitted projects that indicated a good understanding of psychology research design, and indicated that the research experience was acceptable. Alcohol intoxication goggles systematically increased the time required to complete the field sobriety tests, F(2.1, 166.3) = 141.4, p = <.001, partial η2 = .63, and the number of steps taken off of the line in field sobriety tests, F (1.8, 144.8) = 85.5, p <. 001, partial η 2 = .52, as a function of the simulated BAC imposed by the goggles. The goggles did not affect driving simulator performance. The class­wide laboratory experience contributed novel findings about visual impairment by alcohol intoxication goggles on different driving­related behavioral tasks. It also provides a method to incorporate hands­on research experiences as a regular part of an undergraduate psychology research methods course and furthers understanding of the utility of alcohol intoxication goggles in laboratory research.

Keywords: alcohol intoxication goggles, BAC goggles, course­based undergraduate research experience, driving simulator, field sobriety test, college students

Hands ­ on experiential learning has been an important and growing part of undergraduate education in STEM fields and has numerous

student benefits (e.g., Ahmad & Al ­ Thani, 2022; Brownell et al., 2015; Lloyd et al., 2019). Obvious benefits include enhanced scientific skills such as a

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deeper understanding of the primary literature, research processes and principles, and ethical conduct as well as competence in data analysis, data interpretation, and presentation skills (Lloyd et al., 2019). Additionally, students can gain clarity of their intended career path (Lloyd et al., 2019) and leverage their research skill sets to enhance their applications for graduate training or employment (Perlman & McCann, 2005). In fact, undergraduate students who conducted research were more likely to pursue graduate degrees than their peers who had not (Bauer & Bennett, 2003; Stoloff et al., 2015).

Considering these potential benefits, the American Association for the Advancement of Science (2011) formally called for the development of course­based undergraduate research experiences (CUREs). CUREs are specifically designed to permit entire classes of undergraduate students to conduct novel scientific research during normal course time (Dolan, 2016). In 2013, a working group with expertise in CURE design designated five distinguishing aspects of a CURE, including: (a) use of scientific processes and practices, (b) exploration of novel scientific questions and discovery of unknown outcomes, (c) potential for the project to be published and/or reported to the broader community, (d) collaborative components amongst students in the course, and (e) iteration of current or previous work (Auchincloss et al., 2014). With the exception of a handful of studies, methods to integrate CUREs into undergraduate psychology programs have been largely unexplored (c.f., Dvorak & HernandezRuiz, 2019; Frankowski, 2021; Hernandez ­ Ruiz & Dvorak, 2020; Sathy et al., 2021; Thibodeau, 2011).

Research experiences in psychology, such as those provided via CUREs, can be an effective method to fulfill programmatic expectations (see Principle 3.8) set forth by the American Psychological Association (APA) for undergraduate degrees in psychology (American Psychological Association, 2011). Recently, the APA published updated recommendations for these guidelines that describes their call for research opportunities as part of students’ experiential learning (American Psychological Association, 2023). To help programs establish and maintain models that follow these recommendations, it may be fruitful for existing programs to publish their methodology.

An important aspect of CUREs is the generation of novel research findings in an area accessible to undergraduate students. The present study was designed to (a) demonstrate to students how to make decisions that allow researchers to evaluate and rule out common threats to internal validity, (b) provide students with opportunities to analyze data at the level of the individual subjects (single­subject or within­subjects designs) or

groups of subjects (between­groups designs), and (c) incorporate enough variability in the project’s design to allow each student to gain experience carrying out a unique and subjectively interesting investigation. Thus, this kind of laboratory experience can benefit students academically while simultaneously broadening the pool of researchers who contribute to the study of psychology and, eventually, to psychologically based interventions to promote healthy behavior and reduce injury in daily life. The research area selected for the present CURE was and effects of simulated alcohol impairment on the performance of behavioral tasks related to driving. Alcohol misuse is among the leading causes of premature death globally (GBD 2016 Alcohol Collaborators, 2018) and in the United States (Pilar et al. 2020), and, in 2010, cost the United States an estimated $249 billion (Sacks et al., 2015). Alcohol use disrupts cognitive functioning involved in the operation of motor vehicles and is a common contributing factor to deadly vehicle collisions worldwide (World Health Organization, 2019) and in the United States (National Center for Statistics and Analysis, 2023). In 2021, more than 39,500 people in the United States died in motor vehicle crashes and 15,650 (nearly 40%) of those deaths involved a driver with a blood alcohol content (BAC) of 0.01 or higher (National Center for Statistics and Analysis, 2023). Studies evaluating alcohol’s effects with human participants have shown that alcohol administration has dose­dependent impairing effects on a range of tasks, including decisionmaking (Davis­Stober, 2019), attention (van Dijken et al., 2020), alertness (Berthelon & Galy, 2020), psychomotor coordination (Drummond­Lage et al., 2018), and operation of motor vehicles (Creaser et al., 2011). In fact, alcohol’s reliable detrimental effects on coordinated motor activities have led to the use of several performance­based screening techniques to judge the severity of alcohol impairment (e.g., standardized field sobriety tests, Downey et al., 2016).

Ethical and logistical considerations can make it difficult to study effects of alcohol impairment on driving behavior experimentally. However, commercially available driving simulators (see Yadav & Velga, 2021, for a review) and alcohol intoxication goggles (e.g., McCartney et al., 2017) provide viable laboratory alternatives. Detrimental effects of alcohol intoxication goggles have been well established in some simple tests (e.g., walk­and­turn field sobriety tests). Indeed, alcohol intoxication goggles are used in various demonstrations (e.g., Hennessy et al., 2006) and preventative training exercises (e.g., Dolenc & Slabe, 2020); however, except for a small number of studies (e.g., McCartney et al., 2017), their use has been largely unexplored for simulated driving behavior, and, to the

best knowledge of the authors, completely unexplored as a method of teaching experimental design as a part of an undergraduate psychology research method courses. The present study provided undergraduate students with hands­on research experience applying content taught in a psychology research methods course to evaluate effects of alcohol intoxication goggles on performance in field sobriety tests and driving simulator trials. The method and results of the study conducted by the students are described below.

Method

Participants

Participants were 83 undergraduate students enrolled in a psychology research methods course across three consecutive semesters: winter 2022 (n = 22), fall 2022 ( n = 35), and winter 2023 ( n = 26) at a midwestern university. Depending on the semester, students were

arranged into two or three laboratory sections of a maximum of 20 students (obtained range was 3 to 19 students in a section per semester). The treatment of participants was consistent with a protocol approved by the Northern Michigan University Institutional Review Board. As a part of the laboratory portion of the class, students earned 20 points per data­collection day (100 points total, 8% of the course grade) for participating in simulated driving trials and field sobriety tests and collecting data on five data­collection days scheduled during five consecutive weekly laboratory meetings. Results from participants with incomplete data from simulated driving trials and field sobriety tests because of absences (n = 23) or because they dropped the class before any data were collected (n = 1) were excluded from the present analysis. Figure 1 shows a consort flowchart of participants in the present research.

FIGURE 1

Consort Flowchart of Study Participants

CONSORT 2010

Flow Diagram

Enrolled in the Course (N = 107)

• Winter 2022 (n = 33)

• Fall 2022 (n = 38)

• Winter 2023 (n = 36)

Randomized (n = 107)

Allocation

Allocated to Group A (n = 27)

• Winter 2022 (n = 8)

• Fall 2022 (n =10)

• Winter 2023 (n = 9)

Allocated to Group B (n = 26)

• Winter 2022 (n = 8)

• Fall 2022 (n =10)

• Winter 2023 (n = 8)

Allocated to Group C (n = 27)

• Winter 2022 (n = 8)

• Fall 2022 (n = 9)

• Winter 2023 (n = 10)

Allocated to Group D (n = 27)

• Winter 2022 (n = 9)

• Fall 2022 (n = 9)

• Winter 2023 (n = 9)

Analyzed (n = 23)

• Winter 2022 (n = 5)

• Fall 2022 (n = 9)

• Winter 2023 (n = 9)

Excluded because of missing data (n = 4)

• Winter 2022 (n = 3)

• Fall 2022 (n = 1)

• Winter 2023 (n = 0)

Analyzed (n = 19)

• Winter 2022 (n = 5)

• Fall 2022 (n = 9)

• Winter 2023 (n = 5)

Excluded because of missing data (n = 7)

• Winter 2022 (n = 3)

• Fall 2022 (n = 1)

• Winter 2023 (n = 3)

Analyzed (n = 21)

• Winter 2022 (n = 6)

• Fall 2022 (n = 9)

• Winter 2023 (n = 6)

Excluded because of missing data (n = 6)

• Winter 2022 (n = 2)

• Fall 2022 (n = 0)

• Winter 2023 (n = 4)

Analyzed (n = 20)

• Winter 2022 (n = 6)

• Fall 2022 (n = 8)

• Winter 2023 (n = 6)

Excluded because of missing data (n = 7)

Winter 2022 (n = 3)

• Fall 2022 (n = 1)

Winter 2023 (n = 3)

Apparatus

Alcohol Intoxication Goggles

Participants completed a series of conditions that differed based on the presence and severity of visual impairment imposed by alcohol intoxication goggles that were designed to simulate effects of different blood alcohol contents (BAC). Depending on the condition, this included wearing no goggles ( – BAC), wearing clear Honeywell UVEX chemistry goggles with no programmed visual impairment (0.00 BAC), or wearing Innocorp ltd. Fatal Vision alcohol intoxication goggles that simulated Mild (White label; < 0.06 BAC) or Severe (Black label; ≥ 0.25 BAC) alcohol impairment.

Field Sobriety Tests

A strip of black and yellow hazard­striped duct tape (2 in. wide) was used to create the 12­ft­long line for the field sobriety tests. The field sobriety test used in the present study was the “Walk and Turn” test (National Highway Traffic Safety Administration, 2023), in which participants are instructed to start with one foot on a line, take nine steps heel­to­toe down the line, pivot on one foot, and take nine steps heel­to­toe back down the line without losing their balance or stepping off of the line. Field sobriety tests took place in a 56­in­wide by 283­in­long hallway adjacent to the room that housed

Number of Students and Order of Conditions per Group by Semester

the driving simulator. This narrow hallway was chosen because it permitted participants to stabilize themselves easily by extending their arms against the walls of the hallway and avoid falling in the event that the alcohol intoxication goggles affected a participant’s balance.

Driving Simulator

A driving simulator (Simuride Professional, Version 2.92.17) was used to conduct driving simulator trials. The driving simulator apparatus included a set of three View Sonic computer monitors, accelerator and brake pedals, steering wheel, seat, automatic gear shift, control keypad, and a speaker to present audio stimuli during the driving trials. The driving simulator presented stimuli corresponding to the driving trial and recorded speed (miles per hour, mph), collisions, and driving with the emergency brake engaged. A duplicate set of three View Sonic monitors that mirrored the set on the driving simulator was set up in an adjacent room to allow other students to view events occurring during the driving sessions in real time.

In the first iteration of the project (winter 2022), one to three students observed and recorded data on lane departures that were not preceded by signaling the lane change in each driving trial by marking check boxes on a data sheet that divided each driving trial into 60 blocks of 1 s each (see example data sheet provided in Supplementary Material A at https://osf.io/9nhye/). This provided students with additional practice with observational data collection and determining interrater reliability. This measurement was discontinued in subsequent iterations of the project because students received a similar experience during field sobriety tests (described below) and student feedback indicated that the requirement to collect unsignaled lanechange data was cumbersome.

Questionnaire Design

Each semester, participants designed and completed a questionnaire (51–60 items, depending on the semester) to identify participant characteristics that could be correlated with other questionnaire measures or behavioral measures that were recorded during datacollection days. Questionnaire items were determined in five steps. First, during the first two laboratory meetings of the semester, the laboratory instructors described the basics of the research project and encouraged students to think about research questions that they might find interesting as their data analysis project. Second, students wrote a list of five potential research questions that would serve as the subject of their data analysis project. Third, the laboratory instructors and their supervising professor (the first author) met and recorded one unique research question per student. Fourth, students were

TABLE 1

asked to write a survey question that could provide information to allow the student’s research question to be answered. Finally, after questionnaire items were drafted for each student’s research question, a draft of the full questionnaire was provided to the students, and they were instructed to edit the questions based on what they had learned in the unit on constructing valid surveys. Questionnaire items included various question formats that were designed by the students (e.g., text entry for open­ended questions, radio buttons with categorical options for “yes/no” forced­choice formats, and radio buttons with a continuous scale for Likert­type and semantic differential formats) and were modified across semesters depending on student interests. Laboratory instructors uploaded the questionnaire items into Qualtrics for data collection.

Pre-Experimental Procedure

Instructions

The laboratory instructors provided participants with basic information about completing and collecting data on all study tasks. Participants were instructed to drive within the posted speed limits visible during driving trials (ranging from 30 to 50 mph). Participants were told that each driving trial lasted for 60 s and that three driving trials would be completed during each of the five consecutive data­collection days. Participants also received instructions for starting the engine, engaging the seatbelt, signaling a turn or lane change, and engaging and disengaging the emergency brake. Finally, participants were instructed not to provide each other with feedback during driving trials and field sobriety tests to minimize the influence of outside factors on performance of participants and observers during data collection.

Driving Trial Training

Each participant first received a brief (2–3 min) training session to familiarize the participant with the experimental apparatus and the basic function of the driving simulator program. In the training session, they were trained to start and stop the engine, engage the seatbelt, signal turns and lane changes, and disengage and engage the emergency brake. In the training session, participants did not wear any goggles and drove on an open highway on a clear day or night without traffic (depending on the time of day used that semester). Participants could ask questions and receive feedback from their laboratory instructor during this training session.

Data Collection Training

Before participating in the research, participants were trained to collect observational data on six measures during “Walk ­ and ­ Turn” field sobriety tests (see

Supplementary Materials B for the data sheet used for data collection). In this training, laboratory instructors modeled how to perform the field sobriety test and how to record the data on the data sheet. Then, each instructor had the participants record data on another student’s performance and provided praise and corrective feedback when appropriate. Observers collected data on the amount of time (in s) taken to complete the field sobriety test, the number of steps taken off the marked line, whether participants correctly stepped heel­to­toe, whether participants correctly performed the turn, whether the participant correctly took nine steps in each direction, and whether the participant completed the task without falling or balancing against the wall. Training was considered complete when student observers scored identical marks on all measures except for time to complete the test, wherein a 1 s difference was tolerated during training.

Experimental Procedure Design and Random Assignment

Each semester, student participants in each laboratory section were randomly assigned to four groups. Groups differed based on the order of exposure to the four conditions and on the condition that was replicated on the fifth day of data collection. Table 1 shows the order of conditions for each group and the number of participants assigned to each group per semester.

Conditions

Four conditions were arranged, which differed based on the level of visual impairment imposed during driving simulator trials and field sobriety tests. In one condition, the –BAC condition, participants completed the behavioral tasks without wearing goggles. In the 0.00 BAC condition, participants completed the behavioral tasks while wearing clear goggles (Honeywell UVEX chemistry goggles). This allowed for an evaluation of effects of wearing any kind of goggles on the behavioral measures collected in this study. In the < 0.06 BAC condition, participants completed the behavioral tasks while wearing Fatal Vision White Label alcohol intoxication goggles that simulated a BAC of less than 0.06. This allowed for an evaluation of effects of goggles that simulated a mild visual impairment on the behavioral measures, a simulated BAC that was less than the legal limit for driving a motor vehicle in the state in which the research was conducted. Finally, in the ≥ 0.25 BAC condition, participants completed the behavioral tasks while wearing Fatal Vision Black Label alcohol intoxication goggles that simulated a BAC greater than 0.25. This allowed for an evaluation of effects of goggles that simulated an extremely high BAC on the behavioral measures in this study.

Field Sobriety Tests

Participants completed and collected data on performance during field sobriety tests across five consecutive weekly laboratory meetings, referred to as data-collection days. In each of these meetings, participants completed one “Walk ­ and ­ Turn” field sobriety test. The visual impairment condition in effect for participants in each group on each day corresponded to the order of conditions shown in Table 1. In the field sobriety tests, participants started with one foot on the yellow and black line and, when appropriate, put on the googles associated with the appropriate condition. The participant was then required to tell the observers that they were ready to start, take nine steps heel­to­toe down the line without stepping off the line, pivot on one foot, take nine steps heel­to­toe back down the line without stepping off the line, and tell the observers that they were finished. Requiring the participant to tell the observers when to start and stop recording provided a start and stop time for the measurement of the duration of the trial and judgements about whether the participant took the correct number of steps in each direction.

Two students served as observers for 26 of the 83 participants (31%) to allow for an evaluation of interrater reliability. In some cases, student observations were incomplete (e.g., the time to complete the test was left blank), leading to some differences in the number of comparisons available for individual items. Overall, reliability was fair but not excellent. Student ratings of the time taken to complete the field sobriety test matched within 1 s on 68 of 104 comparisons (62%), and the mean difference between raters’ scores was 2.2 s (SD = 3.7 s). The number of steps taken off the line matched in 80 of 114 comparisons (70%) and differences averaged 1.3 steps (SD = 3.2). Across all data­collection days in all conditions, agreement on correctly stepping heel­to­toe, performing the turn, taking nine steps each direction, and completing the task without falling or touching the wall were 80, 90, 83, and 86 percent of comparisons, respectively.

Driving Simulator Trials

Three 60 s driving trials were conducted for each participant per laboratory meeting during five consecutive laboratory meetings. Each driving trial required participants to drive on a winter highway course with snow, traffic, and requirements to change lanes to avoid barriers that appeared periodically. The winter driving course was selected because it was a moderately difficult course and because it approximated driving conditions in the local area during the winter semesters. Depending on the semester, the time of day in the driving trial (either daytime or nighttime driving) was manipulated. Participants enrolled in winter

(n = 22) and fall (n = 35) 2022 were exposed to daytime driving trials; participants enrolled in winter 2023 (n = 26) were exposed to nighttime driving trials. The same visual impairment condition was in effect for all three driving trials conducted by participants in a group during a single laboratory meeting and corresponded to the order of condition specified for each day in Table 1. Driving trial data were collected primarily using the Simuride software. At the end of each driving trial, the laboratory instructor would save the results of the trial in a text file with a unique name that included the participant ID, the day of data collection, the number of the driving trial that was just completed, and the date that the trial was completed on (e.g., P97_Day5_T1_03.30.23). The text file provided information on various aspects of the driving trial every 100 ms. The primary dependent variables were the number of collisions that occurred during the trial and the speed of the car during each trial. Low speeds (below 10 mph) were excluded from the calculation of the mean speed in each trial because portions of the trial were spent stationary as the participant prepared to drive at the start of a trial or after a collision (starting the car, putting the car into gear, etc.). These stationary periods were not representative of the overall driving speed in that trial. For purposes of the analyses, the measures of interest for each participant were the mean number of collisions and the mean of the mean speed (excluding periods below 10 mph) across the three driving trials of each condition for each participant.

Student Data-Collection Make-Ups

Periodically, students who missed class because of known or unforeseen circumstances arranged a make­up data­collection day with a laboratory instructor under the appropriate conditions for partial credit. Results from these make­up data­collection days were considered valid and are included alongside data collected during the regularly scheduled laboratory times.

Questionnaire Completion

Data collection for the questionnaire occurred during the lecture portion of the class during the 9th of 14 weeks of class, the week immediately following the final datacollection day. Before completing the questionnaire, participants were instructed to enter their participant ID to allow the laboratory instructors to tie the questionnaire data to the results of the other behavioral measures collected, when appropriate. Participants were reminded that a de­identified version of the questionnaire results would be made available to the class and that they could answer or leave blank any questions at their discretion. After the data were collected from the field

sobriety tests, the driving trials, and the class ­ wide questionnaire, the first author arranged the results into a single excel spreadsheet that could be distributed to the class to allow each student to conduct their final data­analysis project. Before sharing the results with students from the class, the first author replaced each participant ID with a unique randomly generated letter. This provided an additional layer of privacy protection to prevent the possibility that students became familiar with each other’s participant IDs during data collection. The results from the questionnaire are of tertiary interest in the present report, but questionnaire items from the initial semester are provided in Supplementary Material C and de­identified responses are available by contacting the corresponding author.

Student Products

As a part of the class, all students were required to submit a final paper and create and present a poster in a public forum. These products were based on the unique, individual analyses chosen by the students. Examples of the individual analyses were: (a) effects of visual impairment in the driving simulator conditions, (b) effects of visual impairment on performance in the field sobriety tests, (c) the correlation between gender identity and performance in the driving simulator conditions, (d) the correlation between caffeine intake and performance in the driving simulator conditions, and (e) the correlation between political affiliation and performance in the field sobriety tests (a full list of topics is available from the corresponding author upon request). The products were expected to include accurate descriptions of the parts of the project (i.e., introduction, method, results, and conclusion) specific to each student’s unique analysis. Evaluations for the final paper, poster, and poster presentation were based on rubrics made available to the class in the early portion of each semester (see Supplementary Materials D). The last paragraph of the conclusions section of the final paper asked students to “describe what you thought about the research project conducted this semester, whether it helped you learn anything about research methods, and note any aspects of the project that were particularly helpful or could be rearranged for future semesters”. In addition to ratings and comments from anonymized end­of­semester course evaluations collected by the university, responses to this prompt were used as part of the “student reflections” described in the results section described below.

Data Analysis

Data relevant to the present study are organized into two major categories. The first category describes effects of the laboratory experience on a few student indicators

of engagement, learning, and acceptability. The second category evaluates the behavioral measures that were collected and analyzed to determine effects of the alcohol intoxication goggles on performance on field sobriety tests and driving simulator trials. Relevant data from each of these categories will be discussed below.

Results

Student Engagement, Learning, and Acceptability

Evidence of student engagement, learning, and acceptability during the present laboratory arrangement comes from student participation data, student products submitted (posters and final papers), and student reflections (evaluations and statements written about the project submitted as part of the final paper).

Student Engagement

As described above, students were awarded course points for attending laboratory meetings in which data were collected. Across the three semesters, student attendance of data­collection laboratory meetings averaged 96 percent of the 106 students who had not dropped the course before the first data­collection day. No students requested to opt out of participating or data collection during any data­collection day.

Evaluation of Student Products

De­identified samples of student papers and posters can be obtained by contacting the corresponding author. Three of the 107 students who enrolled in the course dropped out of the class before submitting their paper and delivering the poster presentation. Across all three semesters, the remaining 104 students received the following grades for their submitted papers: 37 As, 37 Bs, 16 Cs, 7 Ds, and 7 Fs, and the following grades for their posters and poster presentations: 73 As, 21 Bs, 5 Cs, 1 D, and 4 Fs (note, 3 of 4 failing grades resulted from a failure to deliver the presentation).

There were several strengths of this project, the most notable perhaps being the fact that it allowed students to identify, consider, and rule out common threats to internal validity that are taught in the lecture portion of the class. The lecture potion of the class covered strategies to identify and prevent 12 common threats to internal validity in the design and analysis of psychological research: maturation, history, regression, attrition, testing, instrumentation, design confounds, selection effects, order effects, observer bias, demand characteristics, and placebo effects. The experiment conducted in the present laboratory experience allowed consideration of each of these threats. Individual student projects sometimes focused on whether the research

Toegel, Baranski,

design effectively handled one or more of the threats. For example, a student project that evaluated steps off of the line during the walk and turn test for participants who received each of the two control conditions (–BAC and 0.00 BAC) on the first and last data ­ collection day would provide useful information about potential placebo effects (i.e., no goggles versus goggles with no programmed impairment) and practice effects (i.e., the participant’s first time performing the task versus the fifth time performing the task). This is not to say that all students were successful in thoughtfully considering all threats taught in class as a part of their own analysis. Some student projects lacked consideration of these threats altogether. Nevertheless, the fact that most students were successful in thoughtfully applying class content to a real research experience bodes well for the project and may guide future iterations of laboratory experiences planned in the class.

FIGURE 2

Time to Complete Field Sobriety Tests and Steps Off the Line During Field Sobriety Tests in the Initial Exposure to Each Condition

Main Effect

F(2.1, 166.3) = 141.4, p < .001, ηp 2 = .63

Pairwise Comparisons

–vs 0.00 : p = .848

–vs < 0.06 : p < .001

0.00 vs ≥ 0.06 : p < .001

–vs ≥ 0.25 : p < .001

0.00 vs ≥ 0.25 : p < .001

<0.06 vs ≥ 0.25 : p < .001

Main Effect

F(1.8, 144.8) = 85.5, p < .0001, ηp 2 = .52

Pairwise Comparisons

–vs 0.00 : p = .987

–vs < 0.06 : p = .004

0.00 vs < 0.06 : p = .001

–vs ≥ 0.25 : p < .001

0.00 vs ≥ 0.25 : p < .001

<0.06 vs ≥ 0.25 : p < .001

Note. Symbols show results for individual participants; bars show the mean aggregated across all 83 participants. Statistics included on the graph are from repeated measures ANOVA tests with significant comparisons bolded. Replications are excluded from this figure. Comparisons across visual impairment conditions using the repeated measures ANOVA were statistically significant for latency, F(2.1,166.3) = 141.4, p < .001, partial η2 = .63, and steps off the line, F(1.8, 144.8) = 85.5, p < .001, partial η2 = .52, comparisons. All pairwise comparisons were significant at the level of p < .001 except for the following comparisons: -- vs .00 (top and bottom panels), - vs < .06 (bottom only), .00 vs < .06 (bottom only).

Student Reflections

Another beneficial aspect of this experience was that students were able to create individualized projects that focused on an area of interest to them. Interestbased experiences could help students deepen their understanding of psychological research and can serve as an effective method to build and maintain student interest in the field of psychology (Lloyd et al., 2019). Students planned and completed a wide variety of projects depending on their individual interests. End­of­semester student ratings of the laboratory portion of the class reliably earned above ­ average (i.e., greater than 3) ratings on the 5­point scale (with 5 being the best) in areas of interest (grand mean: 4.16), learning (grand mean: 3.78), and overall rating of the course (grand mean: 3.94) across the 85 students who provided ratings for the laboratory portion of the course. Additionally, the last paragraph of the final paper asked students to reflect on the laboratory experience and comment about what they liked and could be improved upon (example below, contact the corresponding author for the full set of 81 available reflections).

Overall in [class], this experiment has given us a taste of what running our very own research would be like. It shows that we need to be able to do the research, execute the experiment, run the statistics, and present the data promptly. Having students freely able to choose their focus made this study feel much more independent. For this reason, I really think that it is a good learning experience for our first few research projects. Participating in it first­hand I can say that I have learned quite a lot, and would recommend projects like this for other classes as well. (Student from winter 2022)

Although students could usually identify areas that they did not like, or areas where they felt improvement could be made, most students generally thought that the laboratory experience was effective, useful, and enjoyable.

Effects of Alcohol Intoxication Goggles on Behavioral Measures

Field Sobriety Test Performance

The primary outcome measures analyzed for the field sobriety tests are shown in Figures 2, 3, and 4. Figure 2 shows the time required to complete field sobriety tests (top panel) and steps off the line (bottom panel) during field sobriety tests in the initial exposure to each condition aggregated across groups of participants. Visual impairment imposed by the conditions had a graded effect on the amount of time required to complete field

Toegel, Baranski, and Toegel | BAC Goggle

sobriety tests. Participants required a mean (and SD) of 23.3 s (5.3 s) and 22.6 s (5.1 s) to complete the field sobriety tests under our control conditions that arranged no goggles and a simulated BAC of 0.00, respectively. Participants required a mean (and SD) of 30.5 s (7.6 s) to complete the field sobriety test under the simulated BAC < 0.06 condition, and 38.63 s (11.4 s) to complete the test under the simulated BAC of ≥ 0.25 condition. A within ­ subjects repeated measures ANOVA was performed, and a Greenhouse­Geisser correction was made for all main effects due to violations of sphericity. The analysis revealed a significant main effect of visual impairment F(2.1, 166.3) = 141.4, p < .001, partial η2 = .63. Tukey’s multiple comparisons tests were conducted to determine whether pairwise comparisons of the results from the four conditions were statistically significantly different from one another. The comparison of the control conditions (–BAC vs 0.00 BAC) was not significant, indicating that the act of wearing goggles did not increase the number of steps off the line. The tests revealed that all pairwise comparisons, except for those that compared the control conditions, were statistically significant at the p < .001 level. Together these results indicate that (a) visual impairment by alcohol intoxication goggles increased the amount of time required to complete the field sobriety tests relative to the two control conditions, (b) the amount of time required to complete the field sobriety tests increased as a function of the level of visual impairment programmed by alcohol intoxication goggles, and (c) the control conditions did not differentially affect the time required to complete the tests.

The bottom panel of Figure 2 shows that visual impairment imposed by the alcohol intoxication goggles had a graded effect on the steps taken off the line during field sobriety tests. A within ­ subjects repeated measures ANOVA revealed a significant main effect of visual impairment, F(1.8, 144.8) = 88.5, p < .001, partial η2 = .52. Tukey’s multiple comparisons tests revealed that the two control conditions were not significantly different from one another (p = .98), indicating that the act of wearing goggles per se did not increase the number of steps off the line. The number of steps off the line in the < 0.06 BAC condition (M = 2.5, SD = 4.0) was significantly higher than in the – BAC (M = 0.42, SD = 1.8) and 0.00 BAC (M = 0.21, SD = 1.0) control conditions (p = .004 and p = .001 levels, respectively). Significantly more steps off the line were recorded in the ≥ 0.25 BAC condition (M = 8.8, SD = 6.9) than in all three of the other conditions (p < .001 in each comparison). Together these results indicate that (a) steps off the line increased as a direct function of the visual impairment imposed by the alcohol intoxication goggles and that (b) these results were not attributable to solely wearing goggles.

Figure 3 shows the difference in time to complete the field sobriety tests and steps off the line in each participant’s first field sobriety test compared to their final field sobriety test, arranged by group and order of exposure to conditions. The participant IDs used in the top and bottom panels of the graphs correspond to the same individuals. This within­subjects analysis allows the evaluation of practice effects from repeated engagement with the experimental setting and task. The same pattern found in Figure 2 is apparent in this figure; performance was similar in the two control conditions, and the deleterious effects of alcohol intoxication goggles on performance

Time to Complete Field Sobriety Tests and Steps Off the Line During Initial and Repeated Exposures to the Conditions for Individual Participants in Each Group

Note. Symbols each show participant’s latency(s) to complete the walk-and-turn test (top panel) and steps off the line (bottom panel) during the initial exposure (dark) and replication (light) of the first condition. Participant numbers and groups are consistent across panels. Arrows show the direction and extent of changes in the measure after repeated exposure to the Field Sobriety Tests. Dashed lines show the mean aggregated across participants during the initial exposure (long dashes) and replication (short dashes) of conditions.

The Percentage of Field Sobriety Test Components Completed Accurately in Each Condition, Aggregated Across Participants

FIGURE 3

FIGURE 4

generally increased as a direct function of simulated BAC impairment. This figure also shows that after repeated exposure to field sobriety tests, individuals generally took less time to complete the tests and stepped off the line less often while completing the tests; however, even among replications, both the time to complete the tests and steps off the line increased as a function of visual impairment imposed by the alcohol intoxication goggles.

Figure 4 shows participant performance on four additional measures from field sobriety tests, expressed as the percentage of participants that accurately completed each component of the test during their initial exposure to each condition. Performance was generally more accurate under the control conditions compared to conditions with alcohol intoxication goggles, but the component of taking the correct number of steps down and back appeared to be insensitive to the manipulation. Across the other three measures, errors were concentrated primarily in the ≥0.25 BAC condition (23% correct for maintaining balance, 27% correct for pivoting on one foot, and 50% correct for stepping heel­to­toe), followed by the < 0.06 BAC condition (45%

correct for maintaining balance, 59% correct for pivoting on one foot, and 50% correct for stepping heel­to­toe). The relatively low percentage for maintaining balance across all conditions is probably influenced by the low threshold used to measure an error of balance—touching the wall to balance during the field sobriety test. Nonetheless, this threshold was instrumental in our ability to measure this feature of visual impairment safely without requiring that students fall to the ground if they lose their balance. Overall, results from Figure 4 corroborate and extend results from Figures 2 and 3. Performance on the field sobriety test was not affected systematically for one component of the field sobriety tests (correctly taking nine steps down and back) and performance becomes systematically less accurate on three components (stepping heel­to­toe, pivoting, and maintaining balance) as a function of visual impairment by alcohol intoxication goggles.

Driving

Simulator Trial Performance

Figure 5 shows results for the mean (±SD) speed, in miles per hour, and mean (±SD) collisions per driving trial in the initial exposure to each condition, aggregated across the 57 participants who completed the driving course in daytime conditions (gray symbols) and the 26 participants who complete the driving course in nighttime conditions (black symbols). Differences in the number of students exposed to the daytime and nighttime manipulation preclude statistical analyses, but visual inspection provides some insights about patterns in the data. As shown by the similarity in means and high degree of overlap of error bars in the top panel of the figure, participants’ mean speed appears not to have been affected systematically by either the visual impairment condition or whether the driving course was set to daytime or nighttime driving. Given that the participants were instructed to follow the posted speed limit (range 30 to 50 mph) as closely as possible, the similarity in mean speeds across conditions and groups is not surprising.

The mean collisions were also similar across conditions by participants exposed to the daytime and nighttime driving conditions, as illustrated by the gray and black symbols, and overlapping error bars. It may be worth noting that the mean collisions by participants exposed to the daytime driving course appears to have been slightly higher than the means by participants exposed to the nighttime driving course. It is unclear why this would be the case, as the nighttime driving course would appear to have worse visual conditions independent of visual impairment condition. Nevertheless, the high degree of overlap in error bars suggests that these differences are not systematic. Future laboratory experiences in this class may focus on evaluating these kinds of differences and arrange comparisons that permit statistical analyses.

FIGURE 5

Overall, effects of the alcohol intoxication goggle conditions differed based on the test that was arranged and the type of measurement. Performance on almost every walk­and­turn field sobriety test measure was systematically impeded as a function of the visual impairment imposed by the alcohol goggles – performance was generally high (short time to complete, few steps off the line, and steps completed accurately) under conditions with no goggles (–BAC) or clear goggles (0.00 BAC), lower with mild alcohol intoxication goggles (< 0.06 BAC), and even lower with severe alcohol intoxication goggles (≥ 0.25 BAC). Performance on the driving simulator trials was not systematically affected by the visual impairment.

Discussion

The present study provides a method for incorporating CUREs into an undergraduate psychology research methods course and describes the materials and methods used to collect the data, an evaluation of engagement, learning, and acceptability, and effects of the alcohol intoxication goggles on field sobriety tests and driving simulator trials. Overall, students participated in the research experience at high rates, demonstrated good understanding of conducting an experiment in psychology, and indicated that the research experience was acceptable. Results from the BAC goggle manipulation showed that performance on the field sobriety test was reliably impaired as a function of the severity of simulated alcohol intoxication. Performance on driving simulator trials was not reliably affected by the goggles.

A core feature of the CUREs model is that the research that the students take part in asks a novel question with unknown results that has potential utility for the broader community. The results from the evaluation of the alcohol intoxication goggles could be meaningful in at least two ways. First, the finding that performance on the field sobriety tests declined systematically as the simulated alcohol intoxication was raised in the BAC goggles provides some support for the face­validity and effectiveness of the simulated alcohol impairment via BAC goggles on this kind of test. Second, the finding that the alcohol intoxication goggles had no systematic effect on performance in driving simulator trials suggests that the bounds under which these goggles impair behavior depends not only on the simulated BAC in the goggle, but also on the kind of test that is used to measure behavior. It is possible that these differences stem from the requirement to engage in full­body gross motor movement through space. Similar speculation has been posited by others (e.g., Hennessy et al., 2006); however, to date, evidence describing the bounds under which alcohol intoxication goggles are likely to produce observable and systematic effects is scarce. In the present experiment, BAC goggles impaired performance as a function of simulated

BAC during tests that involved a participant moving through space and balancing on a line. When tests involved performing a task while seated, the goggles did not impair performance. Researchers interested in studying effects of alcohol intoxication in the laboratory may need to be thoughtful in their selection of behavioral tasks and might find value in systematic investigations of tasks with differing requirements (e.g., stationary work, limited movement, or gross motor movement) to determine the conditions under which the alcohol intoxication goggles provide valid comparisons to the impairments observed following real alcohol consumption. As more is learned about the bounds under which technology like BAC goggles can aid in laboratory research, the field will gain tools to simulate, and eventually, address problems related alcohol use.

From a teaching perspective, a primary limitation to the present study is the lack of a clear comparison for student learning. One option available to future is the arrangement of a no­CURE control group. Other options that could be implemented in future iterations of the course include the arrangement of a pre­post assessment of (a) a research proposal or poster presentation or (b) a test that evaluates research design and ruling out threats to internal validity. Future evaluations of laboratory experiences might take these limitations and possible solutions into consideration when designing assessments that can provide clear insights into student learning.

An additional design decision that could be considered a limitation was that the students were provided the opportunity to design the questionnaire items themselves each semester based on analyses of interest to them. This resulted in very few questionnaire items that were consistent across semesters, some of which may have been of interest to a broader audience (e.g., basic participant demographic information such as age, sex, and race/ethnicity). Nevertheless, the authors believe that allowing students to design the questionnaire was a critical piece of the laboratory experience, despite it interfering with the detection of significant effects between questionnaire results and behavioral measures. Future studies might consider using this model with larger class sizes or repeating a core set of questions across semesters to increase statistical power.

Conclusions

The present study arranged a hands­on course­based undergraduate research experience that measured behavior under four levels of visual impairment. Results showed that the visual impairment produced by the alcohol intoxication goggles had systematic deleterious effects on performance on the field sobriety test, but not on performance in driving simulator trials. The present study provided an example of a method to incorporate

CUREs into undergraduate training and expand the pool of researchers studying variables related to alcohol use and driving. It is our hope that the growth of programs like CUREs can help produce scientists capable of contributing to the field of psychology and developing effective methods to promote healthy behavior and reduce unnecessary injury.

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Author Note

Forrest Toegel https://orcid.org/0000­0003­4644­5788

Mackenzie Baranski https://orcid.org/0009­0009­8485­8525

Cory Toegel https://orcid.org/0000­0002­9050­8398

We have no conflicts of interest to disclose. Materials for this study can be accessed at https://osf.io/9nhye/. We would like to thank the enthusiastic and dedicated students who participated in this course­based undergraduate research experience. Special thanks to Carson Yahrmarkt, Lexi Dalton, Andrew Hauler, and Jordan Porter for their assistance as instructors for the laboratory portion of the class. Correspondence concerning this article should be addressed to Forrest Toegel, Department of Psychological Science, Northern Michigan University, 1401 Presque Isle Avenue, Marquette, MI 49855. Email: ftoegel@nmu.edu

Depression in Asian

Americans: Does Generational Status and Acculturation Predict Severity and Type of Symptoms?

Anh N. Tang and Sharon M. Flicker* Department of Psychology, California State University, Sacramento

ABSTRACT. Despite being one of the most prevalent mental disorders,accurateidentification and treatment of depression may behinderedbythediversityofsymptompresentationacross,and even within, cultures. This study sought to identify how severity andtypeofdepressivesymptoms(psychologicalvs.somatic)vary byacculturationandgenerationalstatusamongAsianAmericans. A sample of 82 U.S.­born and 81 first­generation participants completed an online anonymous survey (Patient Health Questionnaire, Somatic Symptoms Scale, Vancouver Index of Acculturation).U.S.­bornparticipantsreportedhigherdepression symptom severity than first­generation participants (U = 2,386, p=.002,η2=.06),whichalignedwiththehypotheses.Inconsistent with our hypotheses, somatic symptoms of depression did not differ between U.S.­born and first­generation Asian Americans (U = 2,835, p = .11, η2 = .02). Symptom severity had a weak negative correlation with acculturation to mainstream culture, r(145) = −.23, p = .006, and no correlation with heritage culture orientation,r(145)=−.16,p=.06,whichalsodidnotsupportour predictions.Consistentwithpreviousresearch,depressionseverity washigherinUS.­bornAsianAmericans,butthisdifference did not appear related to acculturation. Future research should seek to understand what aspects of generational status are tied to depressionseverity Althoughprevioustheorizingsuggestedthat Asians express depression more somatically, these findings add confidence to the small body of literature that suggests this is not the case. These findings may help improve the accuracy of diagnosis,leadingtoimprovedtreatmentofdepressionforpatients of Asian heritage.

Keywords: Asian American, depression, somatic symptoms, acculturation, generational status

TẮT. Mặc dù trầm cảm là một trong những chứng rối loạn tâm lý phổ biến nhất, việc xác định và điều trị chứng bệnh nàyvẫngặpphảikhókhăndosựđadạngcủabiểuhiệncủatriệu chứng tuỳ theo từng nền văn hoá khác nhau, và thậm chí biểu hiển khác nhau mặc dù trong cùng một nền văn hoá. Bài nghiên cứunàymuốnxácđịnhmứcđộnghiêmtrọngvàloạitriệuchứng

Diversity badge earned for conducting research focusing on aspects of diversity. Preregistration, Open Data, and Open Materials badges earned for transparent research practices. Preregistration can be viewed at https://aspredicted.org/SR6_Q1T Materials and data can be accessed at https://osf.io/9j542

thành một khảo sát ẩn danh trực tuyến (Patient Health Questionnaire, Somatic Symptoms

Scale, Vancouver Index of Acculturation). Nhóm người sinh ra tại Hoa Kỳ báo cáo mức

độ nghiêm trọng của triệu chứng trầm cảm cao hơn so với nhóm người thế hệ di dân đầu tiên (U = 2386, p = .002, η2 = .059), đúng như dự đoán của giả thuyết. Trái với dự đoán

của chúng tôi, mức độ nghiêm trọng của triệu chứng về thể chất giữa nhóm sinh ra tại

Hoa Kỳ và nhóm di dân thế hệ đầu không có sự khác biệt (U = 2835, p = .11, η2 = .016).

Mức độ nghiêm trọng của triệu chứng trầm cảm có mối tương quan tiêu cực yếu với mức

độ hoà nhập văn hoá Hoa Kỳ, r(145) = −.23, p = .006, và không có mối tương quan với

mức độ hoà nhập văn hoá gốc, r(145) = −.16, p = .06, không như dự đoán của giả thuyết. Đúng theo như kết quả của những nghiên cứu trước đây, mức độ nghiêm trọng của trầm cảm cao hơn ở người gốc Á sinh ra tại Hoa Kỳ, nhưng sự khác biệt này không có sự liên qua đến mức độ hoà nhập văn hoá. Các nghiên cứu tiếp theo trong tương lai nên tìm hiểu xem khía cạnh nào của thế hệ di dân có liên quan đến mức độ nghiêm trọng của triệu chứng trầm cảm. Mặc dù các giả thuyết trước đây cho rằng người châu Á thường biểu hiện trầm cảm qua các triệu chứng thiên về thể chất, kết quả trong bài nghiên cứu này củng cố cho một phần nhỏ các nghiên cứu cho rằng điều này không đúng. Những kết quả từ bài nghiên cứu này có thể giúp nâng cao sự chính xác của việc chẩn đoán, dẫn đến nâng cao phương pháp điều trị trầm cảm cho bệnh nhân gốc Á.

Từ khoá: Người Mỹ gốc Á, trầm cảm, triệu chứng về thể chất, mức độ hoà nhập văn hoá, thế hệ di dân

Depression has often been referred to as the “common cold” of mental disorders for its high global prevalence (Goodwin, 2006). Nearly 280 million people worldwide suffer from this disorder, leading to an estimated 700,000 cases of suicide annually (World Health Organization, n.d.). Depression was reported to be the mental disorder with the second­highest annual prevalence in the United States, only surpassed by anxiety disorders (National Alliance on Mental Illness, n.d.). Despite being one of the most prevalent mental disorders, depression still puzzles many researchers due to its complexity. The symptoms and severity of depression are not universal, despite being a global problem. The differences among and even within various ethnicities/cultures regarding the prevalence and severity of depression remain an ongoing question for researchers.

First­generation immigrants who are born in one country and later migrate to another country make up 13.6% of the U.S. population (United States Census Bureau, 2021). Previous studies have compared the prevalence of depression between immigrant populations and Western­born populations using culturally diverse samples; however, these studies have produced

conflicting results. Although some researchers found that immigrants displayed lower severity and prevalence of mood disorders than Western­born individuals (e.g., Breslau et al., 2007; Salas­Wright et al., 2014), others found that immigrants were more likely to have mood disorders than Western­born individuals (e.g., Missinne & Bracke, 2012). Greater clarity could likely be obtained by focusing on specific immigrant populations rather than immigrants as a monolith.

However, mixed findings have also been reported in studies of depression in the Asian population in the United States, specifically. Approximately 24 million people in the United States identify themselves as Asian or partial­Asian (United States Census Bureau, 2020). This study sought to further our understanding of depression in Asian Americans by teasing apart how severity and type of depressive symptoms relate to generational status and acculturation.

Depression Severity by Generational Status

U.S.­born Asian Americans have been thought to have higher rates of depression than first­generation Asian Americans, and several reasons have been proposed for this difference. One hypothesized reason is that của trầm cảm (tâm lý hoặc thể chất) khác nhau như thế nào khi so sánh dựa theo mức độ hoà nhập văn hoá và thế hệ di dân của cộng đồng người Mỹ gốc Á. Một nhóm mẫu gồm 82 người gốc Á sinh ra tại Hoa Kỳ và 81 người gốc Á di dân đến Hoa Kỳ đã hoàn

U.S. ­ born children of first ­ generation immigrants may be more likely to experience conflicts with their cultural identities. These individuals might lack a sense of belonging as they might feel “not Asian enough” and at the same time “not American enough” (Kim et al., 2006). These long­term stressors may eventually create a chronic state of emotional distress that may relate to increased symptoms of depression in U.S.­born Asians.

In addition, growing up in a Western country, children of first ­ generation Asian immigrants are more likely to adopt Western values and norms while still living under the rules of their parents who believe in traditional Asian norms (Kim et al., 2006). Being expected to behave according to their parents’ traditional values, which include obeying elders, might lead to a state of frustration among U.S.­born children of Asian immigrants. Differences in the expression of love between the two cultures perhaps can also create emotional barriers between Asian immigrant parents and their U.S.­born children. Asian parents are less likely to verbally express their love or display intimate physical gestures (i.e., hugging, kissing) towards their children, which contrasts with the mainstream U.S. culture’s way of showing love (Clayton, 2014). Asian parents are more likely to show their love through acts of service, such as providing food, financial support, or access to better education, etc. (Clayton, 2014). The emotional intimacy behind these actions may not be understood by the U.S.­born children, who may be less able to recognize the demonstrations of love from their immigrant parents or feel a lack of emotional connection.

Additionally, compared to Western­born individuals, first­generation Asian immigrants tend to hold more stigma against mental illnesses (Livingston et al., 2018). This stigma might prevent first­generation immigrant parents from showing support to their children who struggle with emotional and mental problems. Consistent with this idea, Asian American college students reported that they do not receive enough emotional support from their parents and constantly worry about not being able to live up to their parents’ expectations (Greenberger & Chen, 1996). This perceived lack of empathy and family support may thus contribute to the higher severity of depressive symptoms in U.S.­born Asians compared to first­generation Asian immigrants.

However, although some research has found that the lifetime prevalence of major depression in Asians born in the host country is higher than in first ­ generation Asian immigrants (Breslau & Chang, 2006), other studies have failed to replicate these findings. For instance, one study of South Asian Canadians did not find a difference in the prevalence rates of mood disorders between their first­generation and their Canadian­born

subsamples (Islam et al., 2014). Additionally, Takeuchi et al. (2007) only found a higher risk of depressive disorder for U.S.­born Asians than first­generation Asians among female participants. These mixed results indicated that it is still unclear whether being born in the host country constitutes a risk factor for depressive disorder for Asian individuals.

Acculturation and Depression

Acculturation refers to how an immigrant adapts to a new host culture that is different from their origin (Heine, 2020). If generational status relates to depression, acculturation might also be expected to relate to depression. In fact, acculturation might be assumed to be the mechanism by which generational status relates to depression: Given that White U.S. Americans have three times higher rates of depression compared to Asian Americans (Lee et al., 2023), those most influenced by U.S. mainstream culture might accordingly have higher rates of depression. Many researchers have investigated the relationship between acculturation and mental illness. However, again, the findings have been mixed. Although some researchers found that among Asian international students, greater acculturation was associated with better mental health (Meghani & Harvey, 2016; Wang & Mallinckrodt, 2006), others found that higher acculturation level had a negative association with mental well­being among Vietnamese American college students (Nguyen & Peterson, 1993). Meanwhile, Shen and Takeuchi (2001) showed that acculturation did not have any relationship with mental health among employed Chinese Americans.

Shen and Takeuchi (2001) pointed out that perhaps these mixed results were due to differences in the way that each researcher operationalized “acculturation.”

For example, Rahman and Rollock (2004) measured acculturation based on factors of perceived prejudice, social customs, and language usage. Nguyen and Peterson (1993) considered the factor of cultural identity and sense of belonging. A common factor that many researchers have often used to measure acculturation is language (e.g., language preference, host language proficiency; Jang et al., 2005).

Perhaps the mixed results from previous studies stemmed from the use of the unidimensional models of acculturation. Individuals do not necessarily identify themselves strictly with one culture and diminish the other; they may have multiple cultural identities that exist independently of each other ( Ryder et al., 2000). Given this, several researchers have suggested that a unidimensional measurement of acculturation is inappropriate, recommending instead the use of a bidimensional model that measures individuals’ multiple cultural identities independently (Meghani & Harvey,

2016; Wang & Mallinckrodt, 2006). For instance, Berry (1990) theorized four categories of acculturation strategies based on how much individuals value maintaining their heritage culture’s identity and characteristics and how much they value developing and maintaining relationships with the larger society. Measuring acculturation using a bidirectional model may help clarify the previous mixed findings regarding acculturation and depression. The current study measured acculturation using a bidimensional model developed by Ryder et al. (2000), in which the orientation toward host culture and the orientation toward heritage culture are evaluated independently.

Psychological and Somatic Symptoms of Depression

Most studies on depression have assessed participants using scales that focus on psychological symptoms of depression. Although many patients with depression display psychological symptoms, others may have symptoms that are more physically related, called somatic symptoms (Heine, 2020). As Asians are more likely to hold stigmas and negative attitudes toward mental illness than individuals of other races (Eisenberg et al., 2009), there is a possibility that these stigmas may drive Asian individuals to suppress or hide their emotional distress when being evaluated, resulting in fewer reports of psychological symptoms and more reports of somatic symptoms (Anderson & Mayes, 2010). Researchers may inaccurately conclude that their Asian samples have low rates of depression if they exclusively focus on psychological symptoms of depression, to the exclusion of somatic symptoms (Anderson & Mayes, 2010).

Several studies have found greater somatic symptomatology among Asian individuals who are diagnosed with depression. One study observed inpatients diagnosed with depression from 40 psychiatric facilities in six East Asian countries and found that these patients all suffered from pain­related physical symptoms (Novick et al., 2013). Parker et al. (2001) found that patients in Malaysia displayed fewer cognitive symptoms of depression (e.g., feeling worthless or guilty), but significantly more somatic symptoms compared to White patients in Australia. Similar results were also reported in a comparison of patients in China and White patients in Canada (Ryder et al., 2008). This phenomenon was not only prevalent among individuals in Asia but has also been observed in Asian individuals from Western countries. Consistent with the results from Asia, Westerners of Asian heritage have also been found to display more somatic symptoms of depression compared to individuals of other races and ethnicities (Chang et al., 2017; Huynh, 2012).

However, several studies have produced contradictory findings. Kalibatseva et al. (2014) found that Chinese Americans did not show significantly more somatic symptoms than White Americans. In fact, a similarly designed study found that Chinese Americans have fewer somatic symptoms compared to their White counterparts (Kalibatseva & Leong, 2018). Differences in the prevalence of somatic symptoms by generational status have also previously been examined, again with mixed findings. Although U.S.­born Chinese Americans reported more somatic symptoms compared to their foreign­born counterparts (Zhu, 2018), the same effect did not hold for U.S.­born Filipinos compared to first­generation Filipino immigrants (Mossakowski, 2007). These mixed results imply that it is still unclear whether somatic symptoms are more prevalent in Asian individuals compared to individuals of other ethnicities, and whether somatic symptoms differ by generational status among Asian Americans.

Current Study

In sum, previous findings regarding the severity and nature of depressive symptoms in U.S.­born and first­generation Asian Americans have been mixed. Whether acculturation is related to the severity of depression symptoms is also still unclear. Improving our understanding of how depression may present differently in U.S.­born and first­generation Asian Americans is important for mental health professionals to more accurately diagnose and treat these populations. To this end, this study sought to examine four hypotheses: U.S.­born Asian Americans report greater severity of general depressive symptoms than first­generation Asian Americans (H1); first­generation participants report more somatic symptoms than U.S.­born participants (H2); those more highly acculturated to mainstream American culture report more general depressive symptoms (H3); those more orientated toward their heritage culture report less general depressive symptoms (H4).

The fourth hypothesis was not part of the study’s original preregistration ( https://aspredicted.org/ SR6_Q1T). It was added to be more consistent with the Vancouver Index of Acculturation (VIA) scale, which emphasizes a bidimensional model of acculturation, measuring orientation toward heritage culture and orientation toward host culture independently. The data were collected but had yet to be analyzed at the time of this change.

Method

Participants

Participants in the study were Asian individuals living in the United States. Most participants were recruited

through online recruitment and snowball sampling ( n = 190). Other participants ( n = 27) were college students in Northern California who completed the survey through the university research website for course credit. In total, 217 participants started the survey. Ten participants did not meet the inclusion criteria: three participants did not report living in the United States, and seven participants did not self­identify as Asian. A total of 44 participants were excluded for the following reasons: 16 participants opened the survey but did not provide any data, 22 participants began the survey but did not provide sufficient data to be included in any analyses, and 6 responses were excluded due to multiple participations and/or nonsensical responses. The removal of these participants from the data set resulted in a final sample size of 163 participants, which based on the a priori power analysis described below, was more than sufficient to test the study hypotheses. Among these individuals, several only provided partial data but could still be included to test certain hypotheses. Participants’ ages ranged from 14 to 59. Eighteen participants did not report their age. Almost two­thirds of the sample were women, just under one­third were men, and 4% identified as nonbinary or other. Table 1 displays the characteristics of the total sample and generational status subsamples.

Measures

Predictor Variables

Generational Status. The participants were asked to answer “yes” or “no” to the question “Were you born in the US?” Participants answering “yes” were categorized as “U.S.­born.” Participants answering “no” were categorized as “First Generation.” Acculturation. The Vancouver Index of Acculturation (VIA; Ryder et al., 2000) is a 20­item instrument in which participants are asked to rate their degree of agreement to scale items from 1 (disagree) to 9 (agree). The scale includes two subscales: 10 items assess participants’ connection to their heritage culture (e.g., “I believe in the values of my heritage culture,” “I am interested in having friends from my heritage culture”) and 10 items assess their connection to mainstream American culture (e.g., “I believe in mainstream American values,” “I am interested in having white American friends”). Items were averaged within each subscale with higher scores reflecting a higher orientation to that culture. Cronbach’s alphas for the Heritage subscale and Mainstream subscale in the current sample were .87 and .85, respectively.

Outcome Variables

General Symptoms of Depression. The Patient Health Questionnaire (PHQ­9; Kroenke et al., 2001) is one of

the most commonly used screening tools for depression (Beard et al., 2016). It asks participants to rate how often they have been bothered by symptoms of depression during the past two weeks. The scale includes five psychological/cognitive symptoms (assessing lack of interest, depressed mood, negative feelings about self, concentration problems and suicidal ideation) and four somatic symptoms (assessing problems with sleep, feeling tired/low energy, excessive or diminished appetite, and psychomotor agitation/retardation; Smolderen et al., 2009). Participants were asked to rate the nine symptoms on a scale from 0 to 3 (0 = not at all, 1 = several days, 2 = more than half the days , 3 = nearly every day ). Cronbach’s alpha in the current sample was .90.

Somatic Symptoms. The Somatic Symptoms Scale (SSS­8; Gierk et al., 2014) asks participants to describe how much they have been bothered by eight physical symptoms (e.g., “feeling tired or having low energy,” “pain in your arms, legs, or joints”) on a Likert­type scale ranging from 0 to 4 (0 = not at all, 1 = a little bit, 2 = somewhat, 3 = quite a bit, 4 = very much) during the past 7 days. Cronbach’s alpha in the current sample was .83.

Procedure

The study was approved by the institutional review board at California State University at Sacramento Tang and Flicker | Depression in Asian Americans

TABLE 1

Note * p < .001. Differences in sample characteristics between U.S.-born and firstgeneration subsamples were tested via t tests (age & acculturation) and chi-square (Asian subgroups & gender).

and was preregistered prior to data collection (https:// aspredicted.org/SR6_Q1T). A research invitation with the link to a Qualtrics survey was sent to multiple internet platforms such as Facebook, Reddit, Discord, etc. The keyword “Asian” and other related keywords such as “Vietnamese,” “Chinese,” “Filipino,” “Hmong,” etc., were used to seek online forums whose members might meet the criteria for the target sample of the study. A copy of the questions from the survey can be found at https://osf.io/9j542 A Vietnamese translation of the invitation was also included when the invitation was posted on Vietnamese ­ dominated online forums (however, the survey was only available in English). The study was also available on the psychology department research participant pool website. To recruit students who met the inclusion criteria of self­identifying as Asian, the university research website utilized screening questions, and only students who identified as Asian were able to see and access this study. All participants accessed and completed the anonymous online survey through Qualtrics. To confirm that participants selfidentified as Asian, the first question on the survey asked participants to identify their racial/ethnic heritage, and those who did not select the option “Asian” were exited from the survey. Students who completed the survey through the university research website received research participation credit for their courses. Participants recruited online did not receive incentives.

Data Analysis

An a priori power analysis was performed using the statistical power calculator G*Power 3.1. A sample size of at least 51 for each of the two groups was deemed necessary for the proposed t tests to detect a medium effect with a power level of 80% and a significance level of .05. Additionally, a sample size of at least 67 was deemed necessary for detecting a correlation coefficient of ± .30, with a power level of 80% and a significance level of .05. Thus, a minimum sample size of 102 was planned, with at least 51 U.S.­born and 51 foreign­born Asians.

SPSS 27 was used to organize the data and analyze the results. The data can be found here. To test the first and second hypotheses, Mann­Whitney U­tests were used to compare the differences in general depressive symptoms (PHQ­9) and in somatic symptoms (SSS8) between the first ­ generation subsample and the U.S.­born subsample. Spearman correlations between acculturation (VIA) and severity of general depressive symptoms (PHQ­9) were examined to test the third and fourth hypotheses. The p values were adjusted for multiple testing using the Benjamini­Hochberg false discovery rate method (Benjamini & Hochberg, 1995). The new threshold value after adjustment was .006.

Results

Kolmogorov­Smirnov tests of normality were conducted to determine whether data for general depressive symptoms, somatic symptoms, and acculturation were normally distributed. The results indicated that data for general depressive symptoms (p < .001), somatic symptoms (p < .001), and heritage culture orientation (p = .03) were not normally distributed. In contrast, the data for American culture acculturation were normally distributed ( p = .20). However, the skewness of the nonnormally distributed data was at a moderate level (.61, .65, and −.51, respectively). As assessed by Levene’s test for equality of variances, there was homogeneity of variances for all the variables: general depressive symptom severity (p = .14), somatic symptoms (p = .06), heritage culture orientation (p = .39), and American culture acculturation (p = .21). One outlier was detected. It was not extreme and did not significantly impact the results; thus, it was not removed. These results led to the decision to use nonparametric tests (i.e., Mann­Whitney U­test and Spearman’s rank correlation) to analyze the data. First ­ generation participants ( M = 31.96, SD = 11.26) were significantly older in age than U.S.born participants (M = 24.59, SD = 7.45) t(143) = 4.68, p < .001. There was no significant difference regarding gender between the two subsamples, χ2(3, N = 163) = 3.39, p = .34. The whole sample was predominately Southeast Asian. However, although first­generation participants in this sample were more likely to be Southeast Asian (91.4%), U.S.­born individuals in this sample were more likely to identify as multiethnic (19.5%) or East Asian (9.8%), χ2(4, N = 163) = 23.96, p < .001. As expected, first ­ generation participants ( M = 7.08, SD = 1.53) reported higher heritage orientation compared to U.S.born participants (M = 6.14, SD = 1.37), t(145) = 3.91, p < .001. However, there was no significant difference in American orientation between the two subsamples, t(145) = −0.93, p = .36.

Hypotheses Testing

Table 2 includes descriptive statistics as well as correlations between study variables. A Mann­Whitney U ­ test was performed to test the first hypothesis, which predicted that the severity of general depressive symptoms in the U.S.­born subsample would be higher than in the first­generation subsample. The severity of general depressive symptoms in the U.S.­born subsample ( Mdn = 9) was found to be higher than in the firstgeneration subsample (Mdn = 7; U = 2,386, p = .002, η2 = .06). Thus, the first hypothesis was supported. A Mann­Whitney U­test was also performed to test the second hypothesis, which predicted that firstgeneration participants would report more somatic

symptoms than U.S.­born participants. Although the results showed that the U.S.­born participants (Mdn = 9) reported more somatic symptoms compared to the first­generation participants (Mdn = 8), the difference was not statistically significant (U = 2,835, p = .11, η2 = .02). Thus, the second hypothesis was not supported.

A Spearman’s rank correlation coefficient was computed to test the third hypothesis, which predicted that acculturation to mainstream American culture would positively correlate with the severity of general depressive symptoms. There was a weak, but significant negative correlation between the acculturation to mainstream American culture and the severity of general depressive symptoms, r(145) = .23, p = .006, 95% CI [ .38, .07], which was in the opposite direction of our prediction. Thus, the third hypothesis was not supported.

Finally, a Spearman’s rank correlation coefficient was computed to test the fourth hypothesis, which predicted that orientation toward heritage culture would have a negative correlation with the severity of general depressive symptoms. No correlation was found between the orientation toward heritage culture and the severity of general depressive symptoms, r(145) = −.16, p = .06, 95% CI [−.31, .01]. Thus, the fourth hypothesis was not supported.

Follow-Up Analyses

Because the PHQ­9 includes both psychological/cognitive symptoms and somatic symptoms of depression, it remains unclear whether psychological/cognitive symptoms differ by generational status or acculturation when we use the total score of the PHQ­9. We thought it would be worthwhile to test whether the same pattern of results held when examining only the psychological/ cognitive symptoms from the PHQ­9. We therefore created two PHQ­9 subscales: one composed of only psychological/cognitive symptoms and one composed of only somatic symptoms, and repeated the analyses.

The results were identical when using the psychological/cognitive symptoms subscale of the PHQ­9 as when using the total score. For H1, U.S.­born participants (Mdn = 5) reported significantly higher scores on the psychological/cognitive symptom subscale of the PHQ­9 compared to the first­generation participants (Mdn = 3; U = 2,477, p = .005, η2 = .05). For H2, U.S.­born participants (Mdn = 5) reported significantly higher scores on the somatic symptom subscale of the PHQ­9 compared to the first­generation participants (Mdn = 3; U = 2,426, p = .003, η2 = .05). This result was similar to the analyses using the Somatic Symptoms Scale (SSS­8) However, it did not reach the level of significance. For H3 and H4, the PHQ­9 psychological/cognitive symptom subscale negatively correlated with acculturation to mainstream American culture, r(145) = .27, p = .001,

95% CI [−.41, −.11], and was unrelated to orientation to heritage culture (p = .10, 95% CI [−.29, .03]). As an aside, neither mainstream culture acculturation (p = .07, 95% CI [−.30, .01]) nor heritage culture orientation (p = .06, 95% CI [−.31, .01]) was significantly correlated with the PHQ ­ 9 somatic subscale. Because we did not hypothesize a relation between acculturation and somatic symptoms, we had not tested this relation using the SSS­8, and thus we do not compare these findings.

Discussion

The purpose of this study was to compare the severity and type of depression symptoms between first­generation and U.S. ­ born Asian Americans and to determine whether an association exists between symptom severity and acculturation level of these individuals. As predicted, first ­ generation Asian Americans reported lower severity of general depressive symptoms than U.S.­born Asians; however, reports of somatic symptoms did not differ between the two subsamples. Additionally, higher acculturation to the mainstream American culture was unexpectedly linked to fewer general depressive symptoms, whereas no association between heritage culture orientation and general depressive symptom severity was found. These findings are discussed below.

Depression Severity by Generational Status

Previous findings have been split on whether depression is more prevalent in first ­ generation or U.S. ­ born individuals. In this study, U.S.­born Asian Americans reported more severe general symptoms of depression than first­generation individuals. This result is consistent with previous research that has found the lifetime prevalence of major depression in U.S.­born Asians to be higher than in foreign­born Asian Americans (Breslau & Chang, 2006). However, this finding contradicts

TABLE 2

Correlations Between Variables and Descriptive Statistics

Islam et al. (2014) who found no significant difference between first­generation and Canadian­born South Asians. Perhaps differences between living in the U.S. versus living in Canada contributed to the differences in results between these studies. Alternatively, perhaps the reason why the current result is consistent with one previous study and not the other relates to the specific ethnic backgrounds of the participants. Breslau and Chang (2006), whose results were consistent with the current study, had a large number of East and Southeast Asian participants living in the United States, similar to the current sample. In contrast, the participants in Islam et al. (2014), whose results are inconsistent with the current study’s findings, were South Asians living in Canada. The participants of the current study, who were dominantly Southeast Asians, might share several cultural similarities to East Asians, and thus be more likely to produce similar results to Breslau and Chang (2006). South Asians’ cultural values and customs differ from those of East and Southeast Asians and may be thus more likely to produce different results (Shankar, 1998). This highlights the importance of attending to cultural differences within Asian samples.

Since first ­ generation Asian Americans were thought to have stronger Asian culture orientation than U.S.­born Asians, we predicted that they would report more somatic symptoms than U.S.­born Asians. This prediction was based on previous findings that having stronger identification with Asian culture was associated with reports of greater somatic symptoms (e.g., Chang et al., 2017). However, contradicting the hypothesis, there was no significant difference between first­generation Asian Americans and U.S.­born Asians in the current study. This finding is consistent with more recent research that found that depressed Chinese Americans presented with predominantly psychological, rather than somatic, symptoms, which the authors suggested might mark a recent change in symptom reporting among Asian Americans (Yeung et al., 2021). More research is needed to see the extent of this phenomenon: Are there specific populations or specific circumstances under which Asian Americans report more psychological vs. more somatic symptoms of depression? In the meantime, clinicians working with Asian Americans would be wise to assess both types of symptoms of depression.

Acculturation and Depression

Given that, in both the current study and past studies, depressive symptoms were found to be more prevalent among U.S.­born Asians compared to first­generation Asians (e.g., Breslau & Chang, 2006), one would expect that higher orientation to American culture would also be associated with higher severity of depressive

symptoms. Surprisingly, in the current study, higher acculturation to American culture was associated with lower severity of general depressive symptoms in the current study. It is unclear why the result was in the opposite direction as predicted. However, it is worth noting that we expected the mean American orientation score in U.S.­born participants to be higher than first­generation participants but, surprisingly, the American orientation scores were quite similar across the two groups.

Given that adherence to Asian values has been associated with stigma toward mental illness that could potentially translate into lower reporting of depressive symptoms (Anderson & Mayes, 2010), heritage culture orientation was predicted in this study to have a negative correlation to general symptom severity. However, the data revealed that heritage culture orientation did not have any correlation to the severity of general depressive symptoms.

Thus, although U.S.­born Asian Americans reported more depressive symptoms than first­generation Asian Americans, acculturation to mainstream culture did not seem to underpin this finding. Future research should identify what other aspects of the U.S. ­ born Asian American experience might drive reports of greater depressive symptoms. Some factors to be considered include identity concerns such as not feeling “Asian enough” or “American enough ,” lacking a sense of belonging in mainstream America or Asian subcultural communities, and within­family conflict about values and expectations that may be provoked by acculturation differences across generations (Kim et al., 2006).

Limitations and Future Directions

As discussed earlier, first­generation Asian immigrants may hold more stigma against mental illnesses compared to Western­born individuals (Han & Pong, 2015; Livingston et al., 2018). This stigma may result in socialdesirability bias among these participants, leading to the unwillingness to acknowledge depressive symptoms. Thus, it is unclear whether the lower prevalence of general depressive symptoms in first­generation participants truly reflects better mental health or was due to response bias stemming from stigmas. For similar reasons, it is unclear whether the symptom reports from participants who scored higher on the heritage orientation subscale were completely reliable. To address this possible source of bias, future research should assess participants’ attitudes toward mental illness to see if negative attitudes/stigma can predict a pattern of responses among the participants.

Because the survey was written in English, individuals needed to understand English in order to participate. The results might have been different if Asian Americans who do not speak English were included in the sample. Furthermore, this inclusion would enhance the generalizability of the

results to a broader Asian American population. Future research should include translations of the survey into multiple languages to collect data from non­Englishspeaking individuals. On a related note, roughly 75% of participants were Southeast Asians with 45.4% of the sample being full Vietnamese. This reduces the confidence with which we can generalize the results to individuals of other Asian ethnicities. Furthermore, due to this disproportionate representation of this subsample, we were unable to compare symptom severity across Asian subgroups, precluding the identification of any within­group differences.

Additionally, the research invitation stated that the study focuses on Asian Americans; thus, participants were aware that they were being evaluated based on their heritage background. Due to the stigma around mental illnesses, there is a possibility that the participants’ answers might have been more likely to reflect social desirability bias under these conditions. Certain participants might have wanted to reflect positively on the mental health of the Asian population and therefore might have not endorsed their symptoms of depression.

The first­generation participants were significantly older than the U.S.­born participants in this sample. Given that past studies have found that depressive symptoms are more prevalent among younger people (Villarroel & Terlizzi, 2020), the age difference between the two subsamples confounds age and generational status and offers a plausible alternative explanation for the finding that U.S.­born participants reported greater depressive symptomatology. Additionally, firstgeneration participants in this sample were more likely to be Southeast Asian, whereas U.S.­born individuals in this sample were more likely to identify as multiethnic or East Asian. This cultural difference between the subsamples is another potential confound. The potential impact of this confound is unclear, as Southeast Asians have been found to have double the depression risk compared to East Asians in a New York City sample (Misra et al., 2020). The strength of these findings might have been more pronounced without this confounding variable.

Among first ­ generation individuals, their life experiences may vary depending on the age when they migrated to the United States, which may also link to their overall mental well­being. Because first­generation individuals who migrated to the United States at an early age (e.g., infant or toddler) practically grew up in the United States, they may feel more similar to U.S.­born individuals than first ­ generation individuals who arrived at a much older age. First­generation individuals who migrated to the United States under the age of 17 have been found to have an increased risk of higher depression severity (Lee et al., 2020). In addition to age at the time of migration, one’s motivation for migration

Tang and Flicker | Depression in Asian Americans

may be related to both their acculturative strategy (Berry, 1997) and their psychological well­being. For example, a refugee who came to the United States to escape war may have a different experience from someone who came to the country to live with their spouse after marrying an American or to further their education. It should also be noted that the sample mostly represented young and middle adulthood; future research should seek to include the perspectives of older adults. The historical time period during which first­generation Asian Americans migrated may also relate to well ­ being, particularly those who experienced periods of increased anti­Asian sentiment in the United States. For these reasons, future research should consider how age, time period, and motivations for migration are associated with well­being in first­generation individuals.

Conclusion

This study adds to the current literature on depressive symptoms in Asian Americans. U.S. ­ born Asian Americans reported greater depressive symptom severity than those born abroad, but the two groups were similar in the types of depressive symptoms exhibited (cognitive vs. somatic). Surprisingly, acculturation to heritage culture was not related to depressive symptoms, whereas those more acculturated to U.S. culture reported less depressive symptomatology. Future research on this topic should seek to identify what aspects of the U.S. ­ born Asian American experience might drive reports of greater depressive symptoms. Future studies would benefit from including non­English speaking Asian Americans in samples as well as assessing participants’ attitudes toward mental illness and age at migration. The findings from this study may help improve the understanding of how depression relates to generational status and acculturation levels in Asian Americans, thus allowing mental health professionals to more accurately diagnose and thus more effectively treat these individuals.

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Author Note

Sharon M. Flicker https://orcid.org/0000­0002­8228­0987

This study was preregistered at https://aspredicted.org/SR6_Q1T Materials and data can be accessed at https://osf.io/9j542

Positionality Statement: Anh identifies as a Southeast Asian woman

Tang and Flicker | Depression in Asian Americans

born and raised in Vietnam. She moved to the United States at the age of 18 and has continued to live and work within the Asian American community in Northern California for almost 7 years. Sharon identifies as a cisgender White woman, born and raised in the United States, who has lived and worked in East Asia and South Asia for approximately 5 years. They acknowledge that their perspectives are influenced by their positions within all of these dimensions of identity.

Correspondence concerning this article should be addressed to Anh N. Tang, C/O Sharon M. Flicker, Psychology Department, California State University at Sacramento, 6000 J Street Sacramento, CA 95819­6007. Email: anhtang.tna@gmail.com

Intellectual Humility and Investigative Behaviors in Relation to Overclaiming of Knowledge

Emma E. Simpson and Katrina P. Jongman-Sereno* Department of Psychology, Elon University

ABSTRACT. Fake news and other forms of misinformation are becoming increasingly prominent in today’s world (Bowes & Tasimi, 2022). Research has shown that people vary in their susceptibility to believing false information (Zmigrod et al., 2019), but few studies have explored the factors that may aid people in avoiding misinformation. This study examined the relationships among intellectual humility (IH), investigative behaviors, and the tendency to overclaim knowledge of false information. Through an online survey, participants (N = 122) completed the General Intellectual Humility Scale (Leary et al., 2017), an adapted measure of investigative tendencies, and the Overclaiming Questionnaire­150 (Paulhus et al., 2003), a questionnaire that asks participants to indicate their familiarity with existent (e.g., prejudice) and nonexistent topics (e.g., consumer apparatus). Correlational analyses showed that IH was not significantly related to claiming familiarity with either real or fake topics, r(117) = .12, p = .20. However, participants who demonstrated greater IH were more willing than those with lower IH scores to investigate all topics, r(119) = .20, p = .03. Additionally, a negative correlation was found between overclaiming bias and investigative tendencies, suggesting that individuals who wanted to learn more about topics were less likely to overclaim their knowledge, r(103) = ­.40, p < .001. Lastly, no significant relationship was found between IH and overclaiming of knowledge, r(103) = ­.13, p = .18. People who are aware of the connections among these variables may be more likely to fact­check topics they encounter and avoid overclaiming knowledge. These findings have implications for decreasing susceptibility to false information including fake news.

Keywords: intellectual humility, overclaiming of knowledge, investigative tendencies

Today, people in the United States are exposed to an abundance of information each day, some of which is true, but much of which is erroneously formulated by unreliable sources. Fake news has become the overarching term to describe misinformation in the media today, and it is capable of misguiding individuals on a variety of issues (Bowes & Tasimi, 2022; Burel

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et al., 2021). For instance, in the United States false claims circulated during the 2020 presidential election, including the conspiracy that voting machines were rigged to alter election results, which misled many voters and led to widespread distrust (Yen et al., 2020). Similarly, the COVID­19 pandemic generated the spread of numerous myths, including the false assertion that

COVID­19 vaccines could cause side effects as severe as autism, which misinformed the public not only in the United States but in various countries worldwide (Skafle et al., 2022). This illustrates how fake news can engender bias in people’s decision­making and behavior, and highlights the importance of understanding what makes one susceptible to false information.

In an attempt to reduce one’s susceptibility to false information, it is important to learn more about what allows people to discriminate between facts and nonfacts. Previous research has studied how intellectual humility (IH), or one’s openness to the idea that one’s beliefs may be wrong, is related to discernment between true and false information (Bowes & Tasimi, 2022; Koetke, Schumann, Porter, & Smilo­ Morgan, 2022; Leary et al., 2017). The present study aimed to answer whether individual differences in IH may relate to the ability to determine the veracity of information one encounters, and the tendency to overclaim what one believes to be true. By discovering some of the mechanisms that affect the spread of misinformation, one may be able to avoid contributing to the rapid circulation of fake news, and instead, endorse more reliable information (Zmigrod et al., 2019).

Intellectual Humility

Previous studies have investigated individual differences in IH and its defining features. IH is defined as the degree of acceptance that one’s beliefs or opinions may be incorrect (Leary et al., 2017). People who are more intellectually humble tend to be more open to new ideas, engage in more flexible thinking, and are less stubborn overall (Koetke, Schumann, Porter, & Smilo­Morgan, 2022; Spiegel, 2012; Zmigrod et al., 2019). Although IH and intelligence are only moderately related, greater IH is highly associated with more general factual knowledge (Porter et al., 2022; Zmigrod et al., 2019). This may be in part because individuals who are more intellectually humble are more driven to expand their understanding of various topics by exerting more effort to acquire knowledge (Koetke, Schumann, Porter, & Smilo­Morgan, 2022). Additionally, IH is associated with the need for cognition, and moderately linked with metacognition, suggesting that individuals with higher levels may engage in more meaningful or critical thinking patterns (Krumrei ­ Mancuso et al., 2019). Moreover, this may contribute to the ability of those who are higher in IH to make better­informed decisions (Porter et al., 2022).

The key characteristics of IH, including openness and flexibility, can contribute to how one approaches real ­ world issues, especially as applied to certain domains like politics or social issues. For instance,

greater IH has been correlated with a greater willingness to get vaccinated against COVID­19, demonstrating a potential ability to recognize that some information about the negative effects of the vaccine is not supported by evidence (Porter et al., 2022). This may be related to greater openness to new experiences and a subsequent willingness to adopt more preventative health measures in individuals with higher IH (Koetke, Schumann, Porter, & Smilo­Morgan, 2022). Greater IH is also associated with an openness to consider discordant political information, which is important in approaching critical decisions such as deciding who to vote for (Koetke, Schumann, Porter, & Smilo­Morgan, 2022). Openness to different ideas and the capacity to evaluate information critically are increasingly important qualities to have in a society overridden with misinformation and fake news.

Intellectual Humility and Discernment of Information

The ability to fully understand the limitations of one’s knowledge may protect intellectually humble people from cognitive biases in information seeking. People who are high in IH are less likely to be susceptible to false information or rely on confirmation bias when seeking out new ideas (Zmigrod et al., 2019). Research in this area has taken a closer look at how IH relates to better discernment of misinformation, specifically in the form of fake news headlines and non­existent terms (Bowes & Tasimi, 2022; Zmigrod et al, 2019). These studies have shown that having higher IH can reduce one’s susceptibility to fake news and help limit the spread of misinformation (Bowes & Tasimi, 2022). A recent study by Bowes and Tasimi (2022) examined how unique features of IH were related to believing and endorsing misinformation, including fake news, conspiracy theories, and pseudoscience. The main findings showed that IH was negatively correlated with endorsing fake news and positively correlated with endorsing true news headlines. A greater ability to distinguish between true headlines and misinformation was directly related to greater IH (Bowes & Tasimi, 2022). By conducting further research on factors like IH that influence one’s susceptibility to misinformation, ways to avoid making these mistakes throughout daily life may be identified.

Investigative Behaviors

As stated, some past research has linked IH to discernment between true and false information. However, it is not understood which aspects of being intellectually humble lead people to accurately discriminate between true and false information. The present study explored whether the way in which people engage in information ­ seeking behaviors to

acquire knowledge may be one reason for better accuracy. Specifically, engagement in investigative behaviors, activities such as fact­checking, seeking additional information, or simply further researching a topic that is presented may allow people to correctly identify what is true or false in various contexts (Koetke, Schumann, & Porter, 2022).

Researchers have examined investigative behaviors directly in relation to IH, showing that those higher in IH generally tend to engage in these types of behaviors, especially in the face of misinformation (Koetke, Schumann, & Porter, 2022; Koetke, Schumann, Porter, & Smilo­Morgan, 2022). Koetke and colleagues examined this relationship in the context of misinformation about the COVID­19 pandemic and found that when participants were presented with fake news headlines, IH was related to being more likely to engage in investigative behaviors such as fact­checking (Koetke, Schumann, & Porter, 2022 ). This demonstrates the relationship between IH and the likelihood of explicitly seeking out or validating facts when confronted with false information. Koetke, Schumann, Porter, and Smilo ­ Morgan (2022) have also examined the relationship between IH and investigative behaviors in the domain of politics. These findings replicated those of the domain of COVID ­ 19 and revealed that IH was related to further investigation of information, whether or not it was ideologically concordant with the participants’ political beliefs (Koetke, Schumann, Porter, & SmiloMorgan, 2022). This finding suggests an openness to opposing viewpoints, and a willingness to consider opposite political orientations in individuals with higher levels of IH. In addition, this study examined the causal relationship between IH and investigative behaviors. IH was manipulated by asking participants to reflect on their incorrect answers and recognize their personal fallibility through a questionnaire. This activity was able to successfully temporarily increase IH in participants, which then was related to a greater willingness to investigate information further (Koetke, Schumann, Porter, & Smilo­Morgan, 2022). This demonstrated that increased IH can lead people to engage in more investigative behaviors, at least in the context of controversial political headlines. Alternatively, it is possible that, due to IH’s association with informed decision ­ making and more general knowledge (Porter et al., 2022), those with higher levels of IH can better recognize their knowledge limits, which in turn motivates them to investigate topics further. Due to the limited amount of research on this topic, it is unclear what mediates the relationship between IH and investigative behaviors, or whether the association is consistent when applied to other forms of misinformation, such as the overclaiming of knowledge.

Overclaiming of Knowledge

Previous research has established the overclaiming of knowledge as a phenomenon whereby people claim impossible knowledge–familiarity with things that do not exist (Paulhus et al., 2003; Paulhus & Harms, 2004). This phenomenon is surprisingly quite common. Studies have shown that many people overclaim knowledge even when they are warned against it (Paulhus et al., 2003). Overclaiming knowledge also involves discernment between true and false information, similar to the studies on fake news presented above. Certain studies have questioned whether or not overclaiming is related to how people acquire knowledge, but no studies have directly examined this in terms of investigative behaviors (Krumrei­Mancuso et al., 2019). Overclaiming is positively correlated with self­perceived expertise, or the way one views one’s own proficiency in a certain subject area (Atir et al., 2015; Plohl & Musil, 2018). However, this type of “faking” behavior is not an accurate representation of one’s true knowledge. The general tendency of individuals to overestimate their knowledge suggests that people are not good at knowing where their knowledge ends and ignorance begins, and research has shown that people are not accurate judges of their own performance on various skills (Dunning, 2011; Ehrlinger & Dunning, 2003). Limited research has focused on what drives people to fake their competence. People may overclaim to appear more socially desirable in terms of their intelligence, which may benefit them on job applications or aptitude tests (Bing et al., 2011). Correlations also suggest that another reason people may overclaim knowledge is that they are self­righteous, narcissistic, or hold feelings of belief superiority in comparison to others (Leary et al., 2017; Paulhus et al., 2003).

Studies examining the relationship between overclaiming and IH have found that higher IH is negatively correlated with overclaiming knowledge (Deffler et al., 2016; Krumrei­Mancuso et al., 2019). In addition, intellectual arrogance made participants more prone to overclaim their knowledge and abilities (Alfano et al., 2017). Together, these studies show that those with higher IH held more accurate views about what they know (Alfano et al., 2017; Deffler et al., 2016; Krumrei­Mancuso et al., 2019).

Overclaiming and the Dunning-Kruger Effect

Although research on the overclaiming of knowledge is limited, one related concept that is more prominent in research is the Dunning­Kruger effect (Kruger & Dunning, 1999). This effect describes the tendency of people with limited knowledge or competence in a particular domain to overestimate their knowledge of information within that domain (Kruger & Dunning,

1999). Research has shown that people who have greater IH tend to be less susceptible to the Dunning­Kruger effect. For example, Leman and colleagues (2021) asked participants to predict their performance before taking an intelligence test, and those with lower IH overestimated how they performed. This tendency to overestimate their ability demonstrated a susceptibility to the Dunning­Kruger effect, which was greater among individuals with low IH (Leman et al., 2021). These results, along with those of studies that examined IH and overclaiming together, both demonstrate how higher IH tends to correlate with reduced know­it­all tendencies (Krumrei­Mancuso et al., 2019) and overall more conservative views in the assessment of one’s knowledge and performance.

Two key differences exist between the DunningKruger effect and overclaiming of knowledge. First, the Dunning­Kruger effect is partly due to a lack of skill or competence in the areas of information that people are assessed on so that when errors are made, their lack of competence hinders them from recognizing their errors (Kruger & Dunning, 1999). On the other hand, overclaiming of knowledge does not assume anything about one’s levels of intelligence or competence. Second, the Dunning­Kruger effect is a comparison to other people, whereas overclaiming solely focuses on an individual’s own claims of expertise, completely separate from others. Given these differences between the Dunning­Kruger effect and overclaiming, the present study focuses only on overclaiming because we were not interested in how subject area competence or interpersonal comparisons influenced claims of knowledge.

The Present Study

Altogether, an accumulation of past research suggests a connection between IH and information discernment. However, no research has explicitly examined how investigating knowledge further may be related to overclaiming (Krumrei ­ Mancuso et al., 2019). The current study aimed to fill this gap in the existing literature by looking at the connections between IH, engagement in investigative behaviors, and overclaiming.

Given the current research in the areas of our key variables, we hypothesized that certain relationships would exist in the context of this study. First, consistent with Bowes and Tasimi’s (2022) previous findings that greater IH can reduce one’s susceptibility to fake news and lead to more accurate discernment between true and false information, we predicted that greater IH would allow participants to demonstrate better discernment between real and non­existent items on an overclaiming questionnaire compared to individuals with lower IH scores. In terms of investigative behaviors,

we predicted that individuals with greater IH would engage in more investigative tendencies overall, given the findings of Koetke and colleagues that higher IH is associated with further investigating information one encounters (Koetke, Schumann, & Porter, 2022; Koetke, Schumann, Porter, & Smilo ­ Morgan, 2022). Lastly, because past research has demonstrated a negative correlation between overclaiming and IH (Deffler et al., 2016; Krumrei­Mancuso et al., 2019), we predicted that participants with higher scores on the IH measure would overclaim their knowledge in fewer instances than those who demonstrated lower IH.

Method

Participants

The sample for this study was comprised of 123 undergraduate students recruited from the psychology department subject pool at a medium­ sized private university in the American southeast, ranging in age from 18–22 years. Participants were excluded from the analyses if they did not proceed to the end of the survey or if they answered fewer than 75% of the questions. This resulted in one participant being excluded, leaving a sample size of 122. Missing values were excluded pairwise. The mean age among the participants was 19.02 years (SD = 0.87), and most (77%) were in their first year of college. The sample consisted of 82 women, 37 men, and 3 individuals who identified as nonbinary or preferred to self­describe their gender. Additionally, 3 participants identified as transgender. Participants’ race/ethnicity and political ideology are shown in Table 1. Although participants were not financially compensated for their participation, all participants were eligible to receive course credit for completion of the online survey.

Materials and Procedure

Approval was received from the Elon University Institutional Review Board (protocol # 23­164) prior to data collection. The survey was administered in the form of a remote survey with asynchronous participation that could be completed on a computer or mobile phone. Each participant first reported their demographics including age, year in school, race, gender, ethnicity, and religious beliefs. Political ideology was assessed with a single ­ item measure that asked participants, “On the liberal­conservative dimension, how would you rate yourself politically?” Participants could choose from five responses: “very liberal,” “moderately liberal,” “moderate,” “moderately conservative,” or “very conservative.” Participants then answered the six items on the General Intellectual Humility Scale (GIHS) and rated their familiarity with terms from the three pre­selected subscales of the Overclaiming

Questionnaire ­ 150 (Social Science and Law, Life Sciences, and Historical Names and Events). While completing this measure of overclaiming, participants also answered another question following each term that assessed their willingness to investigate the term further.

General Intellectual Humility Scale

Participants completed the GIHS, which uses six items to assess one’s level of IH (Leary et al., 2017). For each question, participants rate the extent to which the item is generally descriptive of them. Answer choices range from 1 (not at all like me) to 5 (very much like me). An example item from the GIHS is, “In the face of conflicting evidence, I am open to changing my opinions.” Overall, higher scores on the GIHS indicate a higher openness to the idea that one’s personal beliefs or opinions may be wrong.

TABLE 1

Demographic Characteristics

Cronbach’s coefficient alpha was .76. The GIHS has been shown to effectively measure IH and correlates positively with related traits such as openness and perspective­taking, demonstrating strong validity (Leary et al., 2017).

Overclaiming Questionnaire-150

The overclaiming scale used in this study is a subset of items from the OCQ­150, which assesses people’s tendency to overclaim in 10 different domains of knowledge (Paulhus et al., 2003). The 150­item questionnaire consists of terms that may or may not be well­known to participants, 30 of which are non­existent foils. Those who take the OCQ150 are asked to rate their familiarity with each term. If the participants claim a degree of familiarity with any of the foil terms, it constitutes some level of overclaiming because the item does not exist. This scale has been used consistently throughout research on overclaiming and has shown not only strong construct validity but also stability in responses over time (Paulhus et al., 2003; Paulhus & Harms, 2004). For this study, only three out of 10 domains were presented to shorten the questionnaire and reduce participant burden, because they answered an additional question about investigative behaviors to accompany each term. We attempted to select three domains that seem most applicable to college students: Social Science and Law, Life Sciences, and Historical Names and Events. Examples of existent terms from these domains include, “behaviorism,” “hemoglobin,” and “Napoleon.” Examples of nonexistent terms include “retroplex” and “consumer apparatus.” Within these three domains, participants rated the extent to which they were familiar with each of the 45 terms on a scale of 0 (not at all) to 4 (extremely). Nine out of 45 total terms were nonexistent foils.

Investigative Behaviors Measure

To determine participants’ willingness to engage in investigative behaviors, they were asked to report their likelihood of further investigating each term they encountered from the OCQ ­ 150. For all 45 terms they were presented with from the OCQ­150, participants also answered the question “How likely are you to spend time learning more about this item?” This was answered on a scale of 1 (extremely unlikely) to 7 (extremely likely). The question and the answer format are adapted from Koetke and colleagues’ (2022) 4­item Investigative Behaviors Measure. This scale’s validity has been demonstrated by its ability to accurately reflect participants’ likelihood of exploring information further and correlates with related constructs like curiosity and willingness to engage with new information. Their measure originally asked participants about their willingness to investigate fake news headlines and

articles, which is not relevant to the context of the present study. We have therefore used their questions as a basis for creating an item that is applicable to investigating real and foil OCQ­150 terms.

Results

Descriptive Statistics

Indices of skewness and kurtosis showed evidence of normal distribution for IH (skewness = ­ 0.78, kurtosis = 2.00), familiarity with real items on the Overclaiming Questionnaire (skewness = ­ 0.70, kurtosis = 1.73), familiarity with fake items on the Overclaiming questionnaire (skewness = 0.84, kurtosis = 1.56), investigating real items on the Overclaiming Questionnaire (skewness = ­0.50, kurtosis = ­0.14), investigating fake items on the Overclaiming questionnaire (skewness = ­0.16, kurtosis = ­0.92), and political ideology (skewness = 0.03, kurtosis = ­0.75).

Participants’ mean scores on the IH scale revealed that overall, they reported being quite high in IH (M = 3.98, SD = 0.50). In terms of familiarity with items on the OCQ ­ 150, participants reported being relatively unfamiliar with topics on the Overclaiming Questionnaire overall. Means and standard deviations of familiarity scores revealed that on average, participants’ familiarity with real versus fake topics on the OCQ­150 differed, but averages for both remained on the lower side of the scale overall (see Table 2). The maximum familiarity with any topic was 3.20 (moderately­somewhat familiar) on a scale of 0– 5, and the average score for all topics in general was only 2.21 (SD = 0.50). A paired­samples t test indicated that participants were significantly more familiar with real topics (M = 2.42, SD = 0.56) than with fake topics (M = 1.42, SD = 0.43) on the Overclaiming Questionnaire, t(116) = 22.26, p < .001.

In general, participants were not very open to further investigating the topics they saw on the Overclaiming Questionnaire ( M = 3.73, SD = 1.07).

A paired­samples t test on the investigative tendencies measure revealed that participants were slightly more likely to want to learn more about real topics ( M = 3.79) than fake ones (M = 3.45), t(118) = 6.87, p < .001, but these average scores indicate that on the 7­point scale, participants tended to be only “slightly unlikely” or “neither likely nor unlikely” to spend more time learning about both real and foil terms they encountered (see Table 2).

Relationships Among IH, Familiarity, and Willingness to Investigate

Pearson correlations were calculated to investigate relationships between IH, familiarity with topics, and willingness to investigate topics (see Table 3). Results

showed that IH was not significantly related to claiming familiarity with the topics, r(116) = .12, p = .20. This was true when looking at correlations with both real, r (116) = .09, p = .34, and fake topics, r (117) = .12, p = .19. However, participants higher in IH were more willing to investigate all topics, r(118) = .20, p = .03. Specifically, analyses revealed a significant relationship between IH and willingness to learn about fake topics, r(118) = .20, p = .03, and a marginal relationship between IH and wanting to learn about real topics r(118) = .18, p = .05. The magnitude of these correlations ranged from small tomedium (Gignac & Szodorai, 2016). Finally, familiarity with all topics was positively correlated with

TABLE 2

Means and Standard Deviations for Topic Familiarity and Willingness to Investigate

Note. Familiarity Real refers to participants’ degree of familiarity with existing topics on the Overclaiming Questionnaire-150. Familiarity Fake refers to participants’ degree of familiarity with non-existent topics on the Overclaiming Questionnaire-150. Familiarity All refers to participants’ degree of familiarity with both existing and non-existent topics on the Overclaiming Questionnaire-150. Investigating Real refers to participants' willingness to further investigate existing topics on the Overclaiming Questionnaire-150. Investigating Fake refers to participants' willingness to further investigate non-existent topics on the Overclaiming Questionnaire-150. Investigating All refers to participants' willingness to further investigate both existing and nonexistent topics on the Overclaiming Questionnaire-150.

TABLE 3

Correlations Between Variables and Descriptive Statistics

willingness to investigate further, r(116) = .49, p < .001, indicating a large effect (Gignac & Szodorai, 2016).

Indices of Overclaiming

To examine overclaiming of knowledge, two indices were calculated. Overclaiming bias (c’) indicates a participant’s tendency to “say yes” or claim they are familiar with items on the OCQ (Goecke et al., 2020). Overclaiming accuracy (d’) reflects participants’ ability to distinguish between existent and nonexistent items on the OCQ (Paulhus et al., 2003). Both indices rely on a hit rate and false alarm rate, which are computed based on the proportion of correct and false familiarity ratings for existent items and foils (Goecke et al., 2020). Pearson correlations were calculated between IH scores and overclaiming bias (c’) and accuracy (d’) scores. No significant relationship was found between IH and overclaiming bias (c’), r(102) = ­.13, p = .18, or IH and overclaiming accuracy (d’), r (102) = .06, p = .55. Next, investigative tendencies were correlated with overclaiming scores, revealing a large negative correlation between overclaiming bias (c’) and investigative tendencies, r(102) = ­.40, p < .001 (Gignac & Szodorai, 2016). This shows that individuals who wanted to learn more about all topics on the Overclaiming Questionnaire were less likely to overclaim their knowledge. Participants’ willingness to investigate all topics was not related to their ability to accurately discern between real and fake items on the OCQ ­ 150 (d’), r(102) = .16, p = .12. However, participants’ willingness to investigate real items was significantly related to their abilities to accurately discern between real and fake items on the OCQ­150 (d’), r(102) = .21, p = .03, indicating a medium effect size. However, no significant relationship was found between OCQ accuracy and willingness to investigate fake items, r (102) = .11, p = .29. This reveals that participants who were better able to discern between real and non­existent items on the OCQ were more willing to investigate real items they encountered than fake ones.

Political Ideology

Pearson correlations were calculated between participants’ self­reported political ideology and IH, familiarity, investigative behaviors, and overclaiming indices (see Table 3). No significant correlation was found between IH and political ideology, r(118) = ­.03, p = .76. However, the more conservative participants were, the less familiar they were with all topics on the OCQ­150, r(114) = ­.18, p = .05, indicating a small effect size (Gignac & Szodorai, 2016). More conservative participants were also less likely to want to learn about all topics in general r(117) = ­.28, p = .002, and were slightly less likely to

investigate fake topics, r(116) = ­0.28, p = .003, than real ones, r(116) = ­.27, p = .003, indicating medium effect sizes (Gignac & Szodorai, 2016).

Participants’ self ­ reported political ideology scores were also correlated with overclaiming bias and accuracy scores. Although no significant relationship was found between overclaiming bias (c’) and political ideology, r(101) = .11, p = .29, Pearson correlations show that more conservative participants were less able to accurately discriminate between real and fake topics (d’), r(101) = ­.41, p < .001, indicating a large effect size (Gignac & Szodorai, 2016).

Discussion

The results of the survey offer insights into people’s tendencies to misconceive information as real even when it is not, as well as individual differences in IH and investigative behaviors. As expected, participants higher in IH were more willing than those lower in IH to investigate all topics on the OCQ, demonstrating that IH is associated with seeking out new information. Importantly, this relationship was driven by the willingness to learn more about fake topics. These results suggest that something about the fake topics may have sparked interest or doubt in participants with higher IH, leading them to want to learn more about these topics. This same pattern was not found for learning more about real topics. Based on past research on IH and investigative studies, this may suggest that individuals with higher IH can better discern between real and nonexistent topics, and are additionally more likely to fact­check topics that they suspect to be fake (Koetke, Schumann, & Porter, 2022). Although more research is needed to identify the root of this pattern, a willingness to learn more may allow individuals higher in IH to revise false beliefs by validating information they encounter, especially false or nonexistent information. Another finding that supported our predictions was a negative relationship between overclaiming bias and investigative tendencies. In other words, individuals who were willing to learn more about all topics were less likely to say they were familiar with the topics. This finding suggests that people who wanted to learn more about the topics may have been more careful to indicate that they were familiar with the topics. Although no studies have directly examined the correlations between overclaiming of knowledge and investigative behaviors, this supports the idea from existing literature that taking additional steps to acquire new knowledge may be able to help people avoid overclaiming (Krumrei­Mancuso et al., 2019). Our results suggest that engaging in investigative behaviors is associated with a reduced tendency to claim knowledge that one does not possess.

Surprisingly, IH was not significantly correlated with overclaiming in this study. This is interesting when compared to trends in past literature, which have identified lower IH as a predictor of overclaiming (Deffler et al., 2016; Krumrei­Mancuso et al., 2019). In addition, this contrasts with a recent study by Bowes and Tasimi (2022) that looked at how unique features of IH were related to believing and endorsing misinformation, including fake news, conspiracy theories, and pseudoscience. The main findings supported that IH was negatively correlated with endorsing fake news and positively correlated with endorsing true news headlines. In other words, a greater ability to distinguish between true headlines and misinformation was directly related to greater IH (Bowes & Tasimi, 2022). Our findings may differ from those of Bowes and Tasimi because we did not explicitly ask participants to distinguish between real and fake terms, considering that participants were unaware that foil terms existed on the OCQ­150. Their ratings of familiarity for both real and nonexistent items may also have been affected by their general familiarity with the subject areas of the three selected OCQ domains.

Additionally, participants demonstrated a general tendency to report on the lower end of the OCQ scale, as the average familiarity score was 1.92 on a 0–5 scale and the maximum familiarity with any topic was 3.58 (moderately­somewhat familiar). However, existing studies using similar OCQs have also shown participants’ tendencies to report low familiarity on the 6­point scale (Goecke et al., 2020). Therefore, our sample aligns with trends from past literature in which participants were not very familiar with items on the scale. Our results may have been due to a genuine lack of familiarity with the topics, or perhaps participants were hesitant to confidently state that they knew about a topic when they were not informed of what the OCQ­150 was measuring. If participants had reported answers higher on the scale, we may have seen a different trend between IH and claiming familiarity with items on the questionnaire.

Interestingly, being more familiar with the topics was related to being more likely to want to learn more. Because our sample was comprised of undergraduate students, they may have been particularly curious. Moreover, familiarity with the topics may have led participants to feel a sense of fluency, leading them to believe learning about familiar topics may be easier or more accessible than learning about unfamiliar topics (Westerman et al., 2015). In terms of demographic findings, those who leaned politically conservative were less familiar with topics overall, less willing to investigate information, and less successful at identifying foil terms. Past research suggests that these results may be due to skepticism towards real information,

in conjunction with a lack of desire to further investigate information one encounters (Koetke, Schumann, Porter, & Smilo­Morgan, 2022).

Finally, no significant relationship was found between IH and familiarity with real or fake topics. Although past research has shown that IH and intelligence are only moderately related, people high in IH tend to have more factual knowledge (Porter et al., 2022; Zmigrod et al., 2019). Because the overclaiming questionnaire presents factual topics (as well as fake topics), that IH is not related to familiarity with real factual topics is surprising.

Limitations and Future Directions

Because this research was done at a medium­sized liberal arts institution in the southeast, the demographics in the sample are limited. Most participants were around the same age (18 to 22 years), White (90.2%), and were all taking the same psychology course. Our sample was also skewed toward left ­ leaning ideologies (46.6%) compared to 34.2% with moderate beliefs and 19.1% with conservative beliefs. Participants tended to perform similarly on the OCQ­150, which may not have been the case with a larger and broader sample of ages, races, religions, and political ideations. This limitation opens up avenues for further research, including possible studies that examine how IH and overclaiming differ among elementary or high­school­aged students, as well as participants who are from older age groups. Given major events occurring in the world today, this knowledge may also apply to new studies surrounding overclaiming or discerning between real and false news headlines concerning the upcoming 2024 election, while also considering the generational differences in political beliefs. It may also be interesting to examine these trends across different cultures or within student populations at Historically Black Colleges and Universities (HBCUs). Given that the historical and cultural significance of HBCUs often leads to higher levels of engagement in social justice and civil rights activities (Allen, 1992), students at those universities may encounter or seek out more news or information in general (whether real or fake) when compared to non­HBCU students. Additionally, the tight­knit communities of HBCUs tend to be less diverse in terms of background, political affiliation, and race when compared with primarily White institutions (Allen, 1992).

Additional limitations may have arisen from the formatting of the survey questions. First, the shortened version of the OCQ ­ 150, in which we only asked participants to rate 45 items as opposed to all 150 for the sake of length, has never previously been utilized in past research. However, many credible research studies have

Intellectual Humility, Investigating, and Overclaiming | Simpson and Jongman-Sereno

found different ways to assess and score overclaiming with real and foil terms using OCQs that are based on the original Overclaiming Questionnaire­150, but are customized for a specific study (Atir et al., 2015; Goecke et al., 2020; Paulhus, 2003). Though the use of subscales in overclaiming research is common (Atir et al., 2015; Goecke et al., 2020; Plohl & Musil, 2018), the domains we chose to provide on the survey may not have provided a comprehensive view of each participant’s overclaiming tendencies, and some participants were likely more familiar with the subject areas than others. In addition, participants may have been more familiar with topics on the OCQ­150 if we had chosen different domains. Furthermore, as the survey presented demographic questions before the questions concerning key variables, answering these identity and ideology­related questions first may have activated participants’ stereotypes or alternative thinking patterns which may have impacted how they responded to measures of overclaiming, IH, or investigative tendencies. If we were to compose and administer the survey again, we would ask for demographic information at the end to account for the impact of item order. Finally, participants reported their own political ideology on a scale from “very liberal” to “very conservative.” Future research should use existing measures of political preferences to further examine the interesting connections between political ideology and discerning nonexistent from existent topics, familiarity, and investigative tendencies.

Lastly, past research has also raised the concern that higher IH may not lead to increased use of investigative behaviors if the information is not personally relevant to the participants (Koetke, Schumann, & Porter, 2022). In cases such as the pandemic or political arguments, people tend to hold strong opinions that they want others to validate, or they may feel like the topic can be applied to their personal health or well­being (Koetke, Schumann, Porter, & Smilo­Morgan, 2022). If people are asked to further investigate information they do not have any personal connection to, they may not be willing to do so, regardless of their IH level. However, this approach has not been previously tested and is therefore a direction that future researchers could take to validate the connection between IH and investigative tendencies.

Overall, the results of this study have implications for discerning between true and false information, and the ability to identify fake news or false claims. Individuals who have higher IH want to learn more about topics which may make them more likely to factcheck, validate, and confirm information they encounter, as well as take extra steps to learn more about various topics. Although IH was not related to overclaiming

in the present study, perhaps people higher in IH’s willingness to learn more will eventually lead them to better discriminate existent from nonexistent or true from false information.

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Author Note

Emma E. Simpson https://orcid.org/0009­0002­9225­6478 Katrina P. Jongman­Sereno https://orcid.org/0000­00025710­4148

Emma E. Simpson is now a Candidate for the MA in Forensic Psychology at The George Washington University. Materials for this study can be accessed at https://osf.io/f2ytz/. We have no conflicts of interest to disclose. This study was supported by the Elon University Elon College Fellows Program. Correspondence concerning this article should be addressed to Emma E. Simpson at 4 Holcomb Hill Rd, West Granby, CT, 06090.

Email: esimpson6@elon.edu

Existential Concerns, Meaning, and College Adjustment Among Undergraduate College Students

William B. Monti1 and Rachel E. Dinero*2

1Department of Psychological and Brain Sciences & Department of Philosophy, Colgate University

2Department of Psychological and Brain Sciences, Colgate University

ABSTRACT. Transitioning to college is a psychologically vulnerable time for students, and existential anxiety (EA) may create additional adjustment challenges. EA describes the psychological distress that can arise from central metaphysical concerns. Established research has highlighted potential sources of EA in college such as social isolation, identity disruption and meaninglessness (Diehl et al., 2018; Jones et al., 2021; Shin & Steger, 2016). This article examines the role of existential anxiety and meaning in relation to college adjustment and the coping process. A survey was administered over 14 weeks with undergraduate students (n = 178) measuring EA, meaning in life, college adjustment, and coping methods. We expected EA and meaninglessness to correspond with worsening college adjustment and predicted Emotion and Avoidant Focused coping to be the most commonly endorsed methods of coping. Pearson’s correlations found a positive relationship between college adjustment and Presence of Meaning, r(177) = .29, p > .001, and a negative relationship with EA, r(177) = ­.36, p > .001. In a linear regression Searching for Meaning, Presence of Meaning, and psychological distress predicted college adjustment, R 2 = .48, F(7, 166) = 23.71, p < .001. We conclude that EA has an indirect relationship to college adjustment through a magnification of existing psychological distress. Similarly, meaning proved to be a powerful variable. These findings present college students as a relevant population for existential psychology as well as highlighting the impact of meaning in existential psychology.

Keywords: existential anxiety, meaning, coping, adjustment, college

For some students, the adjustment to college presents new challenges and stressors (Lu, 1994). This significant period of transformation can raise existential concerns surrounding purpose, passions, and meaning in life (LeSueur, 2019). The goal of this article was to investigate the experience of these existential concerns, their associated impacts on college adjustment, and the coping strategies deployed to deal with such concerns.

Existential Anxiety

Although existential ponderings have been traditionally relegated to the realm of philosophy (Wild, 1960), psychology has increasingly recognized these intangible topics as relevant to a more empirically based field (Leontiev, 2013; Pervin, 1960). With its origins in existentialism, existential psychology focuses on the human experience and motivation, in addition to questions on freedom, death, and meaning (Koole et al.,

Dinero

2006). The metaphysical and intractable nature of these concerns can produce friction or emotional distress, a phenomenon referred to as existential anxiety (EA; Weems et al., 2004). EA was conceptualized originally in philosophical writing through works such as Sartre’s Nausea or Kierkegaard’s The Concept of Anxiety (Sartre, 2000; Kierkegaard, 1980). For more information, refer to Kierkegaard’s Influence on the Social Sciences, particularly the chapters on Irvin Yalom, Ernest Becker, and Rollo May (Stewart, 2016).

EA would later be identified in clinical settings by psychotherapists such as Irvin Yalom and Rollo May (May, 2015; Yalom, 1980). Their initial methodologies focused on individual ­ centered psychotherapy to address exact existential concerns (Yalom, 1980). Similar forms of existential­inspired psychotherapy continue to this day (Vos et al., 2015). At the core of EA is a fundamental gap between one’s knowledge of self and the ragged uncertainty of our existence (Ullmann, 2024). EA is believed to be an extension of personality, coupled with both self­awareness and gaps in our knowledge of the world (Shumaker et al., 2020). In this study, EA was measured via the Existential Concerns Questionnaire (ECQ) as developed by Van Bruggen et al. (2015, 2017, 2018). The ECQ highlights five distinct domains (i.e., death, meaninglessness, guilt, social isolation, and identity; Van Bruggen et al., 2017).

Domains

Death. Heightened concerns about death are suspended in a lack of certainty or control over death (Lehto & Stein, 2009). This is often centered in the realization that one’s own life will eventually come to an end, and that, as humans, our existence is fragile and subject to risk (Tomer & Eliason, 1996). At a baseline, death anxiety is insufficient to raise clinical concern; however, it can present in such a way as to necessitate intervention (Furer & Walker, 2008). Similarly, Terror Management Theory takes an anthropological approach by trying to explain social and cultural behaviors within human societies as an extension of existential predicaments (Greenberg, 2012). The theory proposes that an awareness of our own mortality is a byproduct of whatever advanced consciousness humans may possess. In doing so, the awareness of mortality is processed as a potential threat. Thus, when faced with this mortality awareness, people act in a way as to reduce or evade the discomfort that comes with awareness. Given this, it may be possible that the transition to college creates a confrontation with the awareness of death during a time of growth.

Guilt. For some, the possibility of death can come to represent a conclusive ending point that can create further concerns about the life that one has

lived (Binder, 2022). This manifests as a guilt that one may have left important things undone, failed in their purpose, or otherwise failed to find a purpose (Lucas, 2004). Guilt can also emerge as a result of unfulfilled expectations or accomplishments in addition to a struggle with feelings of directionless or lacking in purpose. As such, heightened concerns about death are often comorbid with fears of existential guilt or lack of meaning (Breitbart, 2017). In a college population students may face pressures to get the most out of their college experience or have difficulty facing pressures of accomplishing something or finding their purpose.

Social Isolation. This refers to a perceived lack of connection to the broader social world (Helm, Jimenez et al., 2020). Here, social isolation is also tied to the inability to share the same perspective as a peer, and thus the futility of complete understanding of another (Yalom, 1980, p. 355). As Yalom wrote, social isolation “derives from the fact that each of us inhabits a world fully known only to ourselves” (2008, p. 121). However, connection and a shared perspective were found in one study to detract from existential feelings of isolation (Pinel et al., 2006). While similar to traditional notions of loneliness, social isolation encompasses an existential component in its engagement with how one may feel wholly isolated in their beliefs and values (Becker, 2014). Social isolation can lead to psychological distress that may be tied to sense of identity (Helm, Medrano et al., 2020). This is particularly relevant with college students, especially first­year students who must work to create new social connections and who reevaluate themselves next to their peers.

Identity. The term identity has come to take on a multifaceted use. In the existential context, identity refers to an understanding of how people view themselves, and how we as agents fit as actors on the stage of life (Koole et al., 2006). Identity has been recognized as an important existential concept even in adolescents that forms how we understand our purpose and the ways in which we rationalize the world around us (Berman et al., 2006). Identity is often tied to career development as well as social connection (Campbell et al., 2019; Meijers & Lengelle, 2012). Both of these are important considerations, given that college can be viewed as a period to make both major career choices and form social connections (Brown et al., 2023). Furthermore, because self­identity has been found to have an impact on adjustment processes, we consider conflicts in identity to be possible contributors to EA (Campbell et al., 2019).

Meaninglessness. All of these previous domains can create symptomatic meaninglessness. The concept of meaning in human lives is a concept that philosophers

and, increasingly, scientists have had to engage with (Metz, 2013). At some level, the meaningful life holds an inherent appeal with clear psychosocial benefits such as reduced stress and adaptive methods of coping (Hooker et al., 2018). Meaning is broadly construed as a possession of perceptibly important things or as a sense of purpose (Dezelic, 2017). Certain forms of psychotherapy have been developed to target meaninglessness as a root cause of psychic unrest given its importance for holistic wellbeing (Wong, 2010). Meaning is difficult to define but here we treat it as a binary variable consisting of the presence of meaning and a tendency to search for meaning (Steger et al., 2008). For an overview of meaning in existential psychology see Batthyany and Russo­Netzer (2014). In college populations, meaninglessness may primarily present alongside career indecision or a lack of purpose (Miller & Rottinghaus, 2014).

Coping With EA

When it comes to existential psychology, EA carries with it a unique set of challenges (Heidenreich et al., 2021). EA intrinsically holds an intangible, if not unresolvable, nature, and due to this, minimal concrete work has focused explicitly on the how people cope with existential concerns or questions. While pioneers of existential psychology pushed for meaning­centered models of psychotherapy, there is a lack of material that focuses on how people work to resolve EA independent of formal clinical intervention (Yalom, 1980). Here we use the transactional model of stress developed by Lazarus and Folkman (1984) in which coping serves as a means to deal with stressful events. The research here examines coping from three independent styles. Emotion focused coping involves the resolution of distressing emotion through strategies such as meditation or substance abuse (Austenfeld & Stanton, 2004). Problem focused coping is the resolution of distress through concrete attempts to resolve the stressor (Baker & Berenbaum, 2007). Avoidant coping involves avoidance or denial of the stressor (Folkman & Lazarus, 1985).

Prior research presents a clear relationship between factors of coping and psychosocial health in college populations (Cousins et al., 2017), such as aspects of wellbeing (Chen, 2016), and suicidality and meaningfulness (Yi et al., 2021). However, there is a definitive lack of material examining coping in response to EA. This dearth extends to the role of coping as a buffer between the effects of EA on college adjustment. However, given the abstract and unsolvable nature of EA, emotion­based coping may be better equipped to confront the experience of EA compared to avoidant or problem­based coping.

EA in College Populations

In the contemporary environment of higher­learning, student well ­ being is vital (Jones et al., 2021). Late teenage years into the early twenties marks a remarkable time of psychological changes (Arnett, 2000). Roughly one third of people in this age range will go off to college in an American context (Arnett, 2000). These psychological changes are especially pertinent in a college population owing to the increased choices, family separation, and responsibility that can be associated with leaving for college (Rice, 1992). Coping is an important moderator of psychosocial wellbeing in college populations. Coping strategies serve as barriers for stress, burnout, and other mental health issues for college students (Stallman et al., 2022; Straud & McNaughton­Cassill, 2019). However, maladaptive coping strategies may be detrimental to adjustment (McNaughton­Cassill et al., 2021).

College students represent a psychosocially vulnerable population, particularly during the initial adjustment process (Eisenberg et al., 2013). College adjustment refers to the process of acclimating to the college environment both academically and socially (Katz & Somers, 2017). These existing vulnerabilities can exacerbate the confrontation with existential topics, thereby producing EA (Didehvar & Wada, 2023). College presents a unique environment for EA to develop. Students face a new environment, major life and career choices, all while being away from home often, for the first time. These factors may create increased concerns about identity, social isolation, and meaninglessness noted previously in college populations. Diehl et al. (2018), for example, identified loneliness, or social isolation, as an important factor in college adjustment. Dezutter et al. (2014) similarly found that dimensions of meaning played a crucial role in psychosocial functioning in a college sample. In one instance, thematic coding of college focus groups showed that social connection, uncertainty of the future, and making meaning were identified as important existential themes (Brown et al., 2023). Furthermore, students coming into college may feel pressure to make the most of their time at college, reflecting a form of existential guilt or otherwise struggle with their own identity (Jones & Abes, 2013). Often, particularly in college populations, meaninglessness presents as lack of direction in career or personal dynamics (Miller & Rottinghaus, 2014). Similarly, research done with first­year Chinese college students found meaning to be a significant predictor of college adjustment (Wei et al., 2024).

In a college environment, existential concerns were found to contribute to suicidal ideation, though coping strategies moderated the presence of suicidality

(Yi et al., 2021). For many, college is a time of what can be, or feel like, life altering decisions in a space where developing teens are granted increased freedoms and responsibilities. EA may then develop as a result of a pressure to make meaningful social and career decisions (Miller & Rottinghaus, 2014), out of a struggle to form social connections, or in a sense of isolation among one’s peers (Helm, Medrano et al., 2020).

Study Aims

The present research aimed to fill existing gaps in the literature on how EA manifests in college populations. Although college students may not seem like a relevant demographic for studying EA given their youth, in actuality, the college population is highly vulnerable to EA (Brown et al., 2023). We additionally aimed to understand how specific coping methods can mitigate the impact of EA on college adjustment. Finally, we hoped that these results may be useful as action research in order to inform programs designed to meet the needs of college students.

Better college adjustment was hypothesized to correlate with lower psychological distress, EA, and greater Presence of Meaning. EA was expected to be correlated with heightened psychological distress and lower Presence of Meaning. When measuring coping subscales, we expected that worse college adjustment would correlate with Problem and Emotion focused coping since Avoidant coping may be more difficult in a residential college experience. We hypothesized that EA would correlate more with Avoidant coping and Emotion Focused coping, but not Problem Focused coping given the intractable nature of EA that fails to present tangible problems for Problem Focused coping. We expected that specific coping methods like Substance Use, Denial, or Emotional Support for example would be highly associated with worse college adjustment and increased EA. For the regressions we expected that college adjustment would be predicted by EA, the Presence of Meaning, psychological distress, and Problem and Emotion Focused coping.

Methods

Recruitment and Demographics

Data was collected from a small liberal ­ arts college in the United States. The study was evaluated and approved by the Colgate University Institutional Review Board prior to data collection. All participants were enrolled undergraduate college students recruited from active psychology department courses eligible to receive class research credit for survey completion. Data were collected via SONA data collection systems. Participants were assigned a unique identifier to dispense

research credit and to protect anonymity. There were 187 responses, of which nine were eliminated due to missing or incomplete data. Out of 178 complete responses, demographic data was available for 149 of the participants (see Table 1). For participants with demographic data, the average age was 18.85 (SD = 0.92). In total, 45.6% of participants were first­year students, though 35.6% of respondents failed to identify their class year. The relative youth of this sample is primarily due to the fact that psychology classes involving a research participation component are skewed towards students in their first two years of college. This may be a benefit though since college students in their first year may experience greater disruption in the college adjustment processes given the lack of time they may have had to acclimate.

Measures

Participants completed an online survey through the Qualtrics platform. Completion was voluntary and did not use the “forced response” option.

Existential Anxiety. EA was measured using the Existential Anxiety Questionnaire (ECQ) An English adaptation of ECQ was used (Van Bruggen et al., 2017). The ECQ was originally developed by Van Bruggen following the five previously introduced conceptual domains (2018). Developed using three rounds of interviews by Van Bruggen and colleagues, the ECQ demonstrated adequate internal consistency in both clinical and nonclinical samples (Van Bruggen, 2017). The current sample demonstrated similarly appropriate reliability ( α = .93). Participants are asked to rate how frequently they may have certain experiences or thoughts on a 5­point Likert scale ranging from 1 (never) to 5 (always). A sample item related to the domain of death

is “It frightens me that at some point in time I will be dead.”

A sample item for the guilt domain is “I worry about not living the life that I could live.” Based on factor analysis in its development the ECQ is considered a unidimensional scale. Thus, although the ECQ includes questions across all five of the theoretical domains, statistical analyses were done using the average score across all questions with higher scores indicating higher EA.

Meaning in Life was measured independently from EA using the Meaning in Life Questionnaire (MLQ; Steger et al., 2006). Although meaninglessness is one of the domains captured by the ECQ, the ECQ is unidimensional. Given the potential significance of meaninglessness, this additional measure was used to enable statistical analysis independent of the ECQ (Steger et al., 2006). An additional strength of using the MLQ is that it measures both the Presence of Meaning and Searching

TABLE 2

Correlations Between All Variables of Interest

3.

4.

5.

6.

7.

8.

4.

5.

6.

8.

9.

Note

TABLE 3

Correlations Between All Coping Subscales of Interest

for Meaning. In its conception, both subscales of the MLQ exhibited Cronbach’s α values above .80 (Steger et al., 2006). The Presence of Meaning category identified participants current sense of having meaning in their lives. Participants ranked their agreeableness with statements such as “I understand my life’s meaning.” Searching for Meaning identified how strongly people move to find meaning, using items such as “I am seeking a purpose or mission for my life.” Participants ranked the statements on a 5­point Likert scale ranging from 1 (disagree strongly) to 5 (agree strongly). For both categories, the mean score was used. Presence of Meaning was scored so that increased scores indicated a greater sense of meaning while increased Searching for Meaning scores indicated a greater tendency to be searching for meaning. In this study, both Presence and Searching subscales were found to be internally consistent in our sample with Cronbach’s α of .84 and .82 respectively.

Psychological Distress . Psychological distress was measured using the DASS­21 (Henry & Crawford, 2005). Developed for nondiagnostic use on a 4­point scale it identifies three distinct subscales of Depression, Anxiety, and Stress. Sample items include; “I found it hard to wind down…” for the Anxiety subscale or “I felt down­hearted and blue…” for the Depression scale. In testing the DASS­21 exhibited a Cronbach’s α of .88. Psychological distress is measured based on these three subscales, with higher scores indicating increased levels of distress. Scores range from 0 (did not at all apply to me) to 3 (applied a great deal). For analyses an average score was computed from the sum of scores from the three subscales referred to here as psychological distress. The DASS­21 was deemed to be internally consistent ( α = .93). The scale for the variable Psychological Distress was from 0 to 21 with increased scores being indicative of greater psychological distress.

Coping Styles. Coping strategies were evaluated using the Brief­COPE. Based on an initially developed 60 ­ item measure this abbreviated 28 ­ item version distinguishes between problem­focused, emotion­focused, and avoidant types of coping (Carver, 1997). Measured on a 4­point scale ranging from 1 (not at all) to 4 (a great deal), the Brief­COPE provides an additional 14 two­item subscales identifying specific types of coping. For example, people are asked how often they have “been making jokes about it” to measure humor or “I’ve been using alcohol or other drugs to help me get through it” to measure substance use. Scale validity was established in Carver (1997) where the subscales exhibited internal consistency with Cronbach’s α values above .50 as deemed acceptable (1997). Scoring was done by computing the average score across problem­focused, emotion­focused, and avoidant types of coping with a scale from 1 to 4. The subscales were

scored by adding the two questions together to have a scale from 2 to 8. Here, the Brief­COPE scale had a Cronbach’s α of .89.

College Adjustment. Participants general adaptation to the college environment was measured using two independent scales. The College Adaptation Test (CAT) is a 19­item measure assessing the experience of adjusting to college (Pennebaker et al., 1990). It uses a 5­point Likert scale ranging from 1 (disagree strongly) to 5 (agree strongly). In its conception, the CAT exhibited a Cronbach’s α of .79 and demonstrated similar reliability with our sample. (α = .75; Pennebaker et al., 1990). A sample item is “I have worried about the impression I make on others.” The CAT was reverse scored so that increasing scores indicate better adjustment.

The College Adaptation Questionnaire (CAQ) measures college adjustment across 18 items that were rated on a 7­point Likert scale from 1 (not at all) to 7 (extremely; Crombag, 1968). A sample item is “I am very satisfied with the course of my studies.” Reliability and validity of the CAQ was externally established (Van Rooijen, 1986). In our sample, the CAQ exhibited a Cronbach’s α of .89. The CAQ uses the average scores with increasing scores indicating better adjust.

Results

Data was analyzed using IBM’s SPSS Statistics program version 29.0.1.0. Data is available at https://osf.io/5a78s.

Descriptive and Correlational Analysis

First, we assessed means, standard deviations, and Pearson’s correlations between all variables of interest (see Table 2). College adjustment (as measured with the CAQ) had a positive correlation with the Presence of Meaning, r(176) = .29, p < .001, and was negatively correlated with Avoidant coping, r(176) = ­33, p < .001. In addition, the CAQ was negatively correlated with EA, r (177) = ­ .36, p < .001, Searching for Meaning, r (176) = ­ .22, p = .003, psychological distress, r(175) = ­.52, p < .001, and Emotion Focused coping, r(177) = ­.22, p = .005.

EA was positively correlated with Searching for Meaning, r(177) = .29, p < .001, psychological distress, r (176) =.63, p < .001, Emotion Focused coping, r(177) =.41, p < .001, and Avoidant coping, r(176) =.43, p < .001. EA was negatively correlated with Presence of Meaning, r (177) = ­ .36, p < .001, and the CAQ, r(177) = ­.36, p < .001.

Coping Subscales

Individual coping subscales outlined in the Brief­COPE were also analyzed (see Table 3). In measuring the college adjustment process, the CAQ was used where increasing

scores indicate better adjustment. Certain positive types of coping were negatively correlated with the CAQ like Venting, r(177) = ­.27, p < .001, and Humor, r(177) = ­.22, p = .004. Certain potentially maladaptive methods were negatively correlated with the CAQ including Self­blame, r(177) = ­.36, p < .001, and Denial, r(177) = ­.23, p = .002. The correlation between worsening college adjustment and Substance Use was only approaching significance, r(177) = ­.14, p = .057. Neither Planning nor Emotional Support were significantly correlated with either college adjustment scales. EA demonstrated a strong positively correlation with Humor, r (178) = .33, p < .001, and Venting, r(177) = .32, p < .001. Certain potentially maladaptive strategies exhibited a strong positive correlation with EA such as Self­blame, r(178) = .48, p < .001, and Denial, r(177) = .31, p < .001. Additionally, there was a weak positive relationship between EA and Substance Use, r(178) = .22, p = .004, as well as Emotional Support, r(177) = .22, p = .003.

TABLE 4

Multiple Linear Regression Predicting College Adjustment (CAT; n = 173)

TABLE 5

Multiple Linear Regression Predicting College Adjustment (CAQ; n = 173)

Note. Adjusted R2 = .29, F(7, 166) = 11.31, p < .001, 95% CI [3.81, 5.85].

Predicting College Adjustment

To test the hypothesis that EA would predict college adjustment we ran a multiple regression predicting college adjustment from EA, Searching for Meaning, psychological distress, Emotion Focused coping, Problem Focused coping, and Avoidant coping. Data were initially scanned to remove participants with significant portions of missing data. Listwise exclusion was used to handle missing values, out of 178 initial participants 173 were used in the regressions. In order to simplify the model, coping subscales were not included in the regression. Independent regressions were used for each measure of college adjustment (i.e., the College Adaptation Test [see Table 4] and the College Adaptation Questionnaire [see Table 5]). The CAT exhibited an adjusted R 2 of .48, F (7, 166) = 23.71, p < .001, 95% CI [2.98, 3.90]. The CAQ had an adjusted R2 of .29, F(7, 166) = 11.31, p < .001.

Contrary to hypotheses, EA was not a significant predictor in either regression. However, in the regression using the CAT both Searching for Meaning and the Presence of Meaning were significant predictors of college adjustment ( β = ­ .16, p = .009; β = .15, p = .014) though this did not hold true using the CAQ. Psychological distress significantly predicted college adjustment in the CAT (β = ­.53, p < .001) and the CAQ (β = ­.52, p < .001). Finally, psychological distress predicted both the CAT (β = ­.53, p < .001) and the CAQ (β = ­.51, p < .001). On both adjustment measures, the three coping subscales did not appear to predict college adjustment.

It is interesting to note that college adjustment as measured through the CAT was better predicted by EA and coping variables than college adjustment as measured through the CAQ. It is unclear what aspect of these college adjustment measures accounts for this difference.

Discussion

The study confirmed hypotheses that college adjustment correlates with lower distress, EA, and more meaning, and that EA correlates with increased distress and lower levels of meaning. As hypothesized, EA correlated with increased Avoidant and Emotion Focused coping but not Problem Focused. Contrary to hypotheses, while college adjustment was minorly correlated with Emotion Focused coping it did not correlate with Problem Focused coping. The regressions confirmed hypotheses that college adjustment is predicted by distress, however the three coping focuses did not predict adjustment. Perhaps most significantly, existential anxiety alone was not predictive of college adjustment.

EA appears to have a negative relationship to college adjustment, though later regressions did not immediately reinforce this. Similarly, college adjustment

was positively correlated with Presence of Meaning and negatively correlated with Searching for Meaning, which is reflective of previous research that found meaning to have a positive academic effect (Wei et al., 2024). These two points, that heightened EA worsens adjustment while meaning supports it, highlights the heavy importance of meaning in influencing EA and college adjustment independently. The importance of meaning may stem from the presence of important activities in student’s lives (Boone et al., 2023), that reflects a connection between extracurriculars and student happiness (King et al., 2021).

Additionally, in line with hypotheses, EA was positively correlated with Emotion Focused coping. emotional and avoidant methods were more strongly correlated with EA however problem­solving styles had a far weaker association which suggests that higher frequencies of emotional and avoidant coping were the primary ways that students dealt with heightened EA (Langle, 2008). This would be appropriately reflective of the unresolvable nature of EA, such that there is no tangibly resolvable problem for Problem Focused coping to target.

There were significant positive correlations between EA, self­blame, and denial indicating that higher levels of EA were associated with these coping methods. We believe this to reflect the inherent difficulty people have with accepting the inexplicable circumstances of their lives. This is because EA is rooted in an uncertainty about ourselves and existence (Van Den Bos, 2009). Because the confrontation with EA is an internal one the approaches people take to coping reflect an internal struggle.

The college adjustment regressions reinforced the strong relationship between college adjustment and psychological distress (Olmstead et al., 2016). Given the CAT regression predicting college adjustment from psychological distress and both domains of meaning, we believe this to be an indicator of the importance of meaning in college adjustment (Garrosa et al., 2017). However, EA was not a strong predictor of either college adjustment scales.

Despite this, other included variables were significant in combination within the regression models. We believe that EA was not a direct predictor, and that it may have played an indirect role in college adjustment by influencing psychological distress, and due to its overlap with the domains of meaningfulness. This notion reflects the theoretical background of key figures such as Yalom that treat the unanswerable nature of these existential answers as innately anxiety­producing. It is likely that EA is not making it difficult to adjust to college but rather that EA is producing psychological distress that is compounding the psychological detriments of poor college adjustment. Additionally, because domains

Monti and Dinero | Existential Concerns, Meaning, and College Adjustment

of meaning had a stronger relationship to college adjustment, it is likely that meaninglessness as a domain of the ECQ was the driving factor behind the ECQ while the other domains were less potent. It may be that the domains of social isolation, guilt, and identity constitute what is prioritized and therefore meaningful in the lives of college students. In a college environment social isolation is most evident in the pressure to create novel social networks and the contrasting sense of distance from childhood social connections and family systems. A sense of guilt is reflected in the chance to make the most of opportunity and pressure to make impactful choices. Both guilt and isolation are two of many factors in college that contribute to a rapidly developing identity These three domains above all may contribute to meaning or meaninglessness in the ECQ that is the most impactful.

Regardless, the conception of meaning played the greatest roll across variables. This suggests that, going forward, meaningfulness or domains measuring meaning should continue to be treated as significant effectors in existential future models, and that the ECQ would benefit from more research into its individual domains.

Overall, despite a limited sample size, all scales demonstrated excellent reliability. The most significant limitation to the study was in the deficient range of diversity in our respondents. Additionally, the study suffered a lack of other demographic data such as socioeconomic and religious status that may limit conclusions. Because the ECQ scale used to measure EA was unidimensional we were unable to distinguish the impact that the individual domains of EA may have had, and instead had to use a variable of general EA. This means that certain domains captured by the ECQ most likely had a far greater effect on other variables. However, the use of the MLQ successfully identified the heightened effect that the concept of meaning played in the formation of EA. Additionally, though the BriefCOPE scale demonstrated validity both in its conception and in our sample, the scale exhibited fluctuating factor structure which may sway values (Solberg et al., 2022). One further consideration is the lack of standardization within the Likert scales used across measures.

Despite these limitations, this work has emphasized the importance of the human concept of meaning, as well as having demonstrated the detrimental effects of meaninglessness. The use of the Brief­COPE reinforces prior research demonstrating the popularity of certain coping methods in college populations while shedding light on how people may use avoidant and emotionally centered methods of coping to deal with existential friction (Brougham et al., 2009). The work done here further reinforces the prior research identifying the concept of meaning as a relevant factor in the lives of college students

(Shin & Steger, 2016). Notably, this research marks the first tangible body of research to our knowledge that examines specific coping methods alongside EA and the concept of meaning. Other work has established emotion focused coping as a response to EA (Abeyta et al., 2015). What we have attempted to do though is to position existential concerns in relation to specific coping strategies such as humor, substance use, and denial. The results suggest a relationship between EA and specific coping strategies that is worth investigating further.

The results from this data set highlight the importance that meaning plays in the college adjustment process. This is important given the connection between a sense of meaning and suicidality (Allen, 2022). Further work in the field of existential psychology should be done to better understand how people cope with existential challenges particularly dealing with specific strategies such as substance use, denial and peer support. Additionally, given the strength of both the presence of, and tendency to search for meaning, further work is called for to evaluate the concept of meaning in both domains as a relevant factor for psychosocial wellness in younger populations. These findings hold important implications for facilitating student wellbeing in college such by addressing social relationships, identity security, and creating meaningful college experiences. Both the importance of meaning and the risk for existential anxiety in college populations should direct further research and standing programs to focus increased attention on the concept of meaning to inform further action research in college communities, and to build on standing programs to facilitate meaning in the population to cater to the specific challenges faced by college students (Baxter Magolda, 2009). Furthermore, both the importance of meaning and the risk for existential anxiety in college populations will play an important role in the realm of suicide prevention programming (Fitzpatrick, 2009; Wong, 2013).

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Author Note

William B. Monti https://orcid.org/0009­0003­2055­4991 Rachel E. Dinero https://orcid.org/0000­0003­4254­7402 Rachel E. Dinero is now at the Department of Psychology at Le Moyne College, Syracuse NY.

We have no conflicts of interest to disclose. Data is available for viewing via https://osf.io/5a78s Correspondence concerning this article may be directed to William B. Monti. Email: wmonti@colgate.edu

The Role of Client Preference for Therapeutic Alliance in Retention in Therapy

Madeline M. Breaux and Jennifer Zwolinski* Department of Psychological Sciences, University of San Diego

ABSTRACT. This study used a delay discounting model to examine the decisions around and preferences for different levels of therapeutic alliance and different lengths of therapy for therapeutically motivated participants. Overall, the level of bond was predicted to impact participants’ decisions about therapy duration with an overall preference for a stronger bond even if it meant lengthening treatment. A total of 105 participants completed an online delayed discounting questionnaire designed to assess at what indifference point in the therapeutic bond clients were willing to switch to a longer therapy. All participants were either currently attending therapy or waiting to attend therapy, and were primarily White and female with an average age of 34.92 years. A series of nonparametric tests were statistically significant for each of the hypotheses (ps < .001) except for 2c. Specifically, findings indicated that participants switched to the longer treatment duration in order to pursue a stronger therapeutic bond when they were offered a short therapy program with an unbonded or neutral therapeutic bond (1a and 1b), and that people needed higher therapeutic alliances to justify switching to longer therapy programs as their durations increased (8–12 weeks; 2a and 2b). Also, contrary to our predictions, people preferred a longer therapy with a lower bonded therapist over a shorter therapy duration with the highest bonded therapist possible (1c), and people discounted the same amount of therapeutic alliance when switching to the 8­ and 12­week programs (2c). These results suggest that therapeutic alliance influences retention, but participants’ motivation to attend therapy may also be a contributing factor. These findings are important for clinicians to consider when forming relationships with their clients, as previous literature has been mixed on the relationship between alliance and retention.

Keywords: therapeutic alliance, client retention, client preferences, therapy length, client motivation

Research has previously indicated that clients value the therapist alliance in therapy (Dimic et al., 2023), specifically clients residing in western countries (Giallorenzo, 2024). However, less is known about how this preference is predictive of the length of time clients are willing to stay in therapy. Considering the research on client preferences for therapeutic alliance (Dimic et al., 2023; Giallorenzo, 2024), the goal of this study was to use a delayed discounting (DD) methodology to investigate the point at which a client chooses a longer therapy to satisfy their preferences for a therapeutic alliance as opposed to a shorter, equally effective therapy with a therapist that does not

necessarily satisfy their alliance preferences. In other words, this study sought to assess at what point clients who are motivated to attend therapy discount (i.e., give up) a therapeutic alliance with their therapist for a shorter duration of therapy.

This study used the Prochaska and Diclemente’s Stages of Change Model (Prochaska & DiClemente, 1983) to examine how people in the Action and Maintenance stages of the readiness model are influenced by different levels of therapeutic alliance when choosing between equally effective shorter and longer therapy programs. The Prochaska and DiClemente’s Stages of Change Model highlights the

stages that people go through when it comes to deciding on, taking action on, and maintaining changes in their lifestyle and cognition that promote improved mental health. These stages include Precontemplation, where the person is in denial that they need help, Contemplation, where the person has some awareness of their problem, Preparation , where the person is ready to change, Action, where the person engages in actions that will bring about change, Maintenance, where the person implements strategies to maintain their progress for a prolonged period of time, and potential Relapse , where the person returns to their unhealthy behavior (Prochaska & Norcross, 2002). This study focused on the Action and the Maintenance stages of therapy by ensuring that all participants were currently receiving or waiting for treatment for symptoms of a mental health condition, whether it be through therapy, medication, hospital and residential treatment programs, or other types of treatment. The Preparation stage was excluded because, although these people are ready to make change, our sample only included people who had already taken action to receive therapeutic treatment (currently receiving or waiting to receive mental health treatment), and hence truly began considering their engagement in therapy, preferences for therapeutic alliance, and therapy duration. Meanwhile, people in the Preparation stage might not have completely processed these preferences yet. It is important to focus on the Action and Maintenance populations when studying client preferences for therapeutic alliance because these stages suggest that the client is approaching therapy with a positive attitude and a willingness to change. In the case of retention, this ensures that it is more likely to be the therapeutic alliance that affects the time clients choose to stay in therapy, not the client’s negative attitude about therapy. This is supported by Brocato (2004), who found that, in a prison population, clients’ willingness to change was positively related to the number of days they spent in treatment, meaning that people who were not ready to make positive changes in their lives to improve their mental health were more likely to drop out of therapy. Client motivation, such as those who are currently in treatment, therefore, may play a role in making this population want to attend therapy for longer than clients who are unmotivated.

One factor that might influence dropout in clients who are already motivated to attend therapy is the therapeutic alliance, or the bond between the client and the therapist within therapy. Research has shown that clients’ pretherapy motivation to attend therapy influences the client–therapist alliance within therapy, although findings have been mixed. For example, Calsyn et al. (2006), Meier et al. (2005), and Cheng et al. (2010)

and Zwolinski

found that, when clients are motivated to attend therapy, their perception of the therapeutic alliance increases. It is important to keep these findings in mind when studying people in the Action and Maintenance stages because these therapeutically motivated clients may be uniquely influenced by the therapeutic alliance when they are making decisions about how long they are willing to attend therapy.

The client–therapist alliance is an important factor of therapy to study, as multiple meta ­ analyses have shown moderate but positive significant relationships between the therapeutic alliance and positive outcomes in therapy (Flückiger et al., 2018; Martin et al., 2000). One specific study that showed this relationship was Levin et al. (2024), who found that, when depressed clients in a therapy trial rated their therapeutic alliance over time, the level of alliance (i.e., bond) tended to predict their depression scores (with depression scores decreasing as their therapeutic alliance increased).

Additionally, findings have shown that a higher therapeutic alliance could increase client retention in therapy. A meta­analysis (Sharf et al., 2010) found a moderately strong negative relationship between the therapeutic relationship and client dropout rates, signifying that a stronger therapeutic alliance leads to lower dropout rates. Meier et al. (2024) also found this relationship, suggesting that higher alliance scores and lower client distress are associated with longer attendance in therapy. Furthermore, Sijercic et al. (2021) showed that the overall therapeutic alliance positively affects client retention in cognitive processing therapy for patients with PTSD symptoms, although ratings of the initial alliance, late alliance, and change in alliance over time did not predict retention. These findings reinforce the need for therapists to form a strong therapeutic relationship early in the therapy process. However, the findings on the association between therapeutic alliance and client retention are mixed. Some studies have found that the therapeutic alliance predicts retention in some cases but not others, such as Barber et al. (2001), which found that the relationship between therapeutic alliance and retention for people struggling with cocaine addiction depended on the type of treatment given. In this study, people who were given supportive­expressive therapy and individual drug counseling treatments showed a positive relationship between bond and retention (higher bond, higher retention) or no relationship between therapeutic bond and retention, and cognitive therapy treatments showed a negative relationship between therapeutic alliance and retention (higher bond, less retention). Finally, research has also indicated that there is no relationship between therapeutic alliance and retention, such as Brocato

(2004), who found that therapeutic alliance was not a predictor of client retention in therapy in a prison substance abuse program. Because all of these studies consisted of different conditions, a better understanding of the conditions that impact direction or degree of the relationship between alliance and retention is needed.

Time, or length of treatment, is one of these variables that needs further investigation as it relates to alliance, given that creating a therapeutic alliance takes time. For example, Prusiński (2024) found that, for adults with adaptation disorders, the therapeutic alliance increased by a stable linear trend over time throughout the course of a year’s worth of therapy for individuals whose therapy was successful, and that stronger alliance correlates with better treatment outcomes. Furthermore, Littauer et al. (2005) found that most clients needed two sessions, on average, before a good or very good alliance with their therapist was created. Overall, therapeutic alliance is a predictor of positive therapeutic outcomes and longer attendance in therapy; however, this can take time to build.

It is important to look at how time influences the therapeutic bond because client premature termination of therapy is a problem within psychotherapy (Sijercic et al., 2021), and clients often drop out early because they do not feel a strong bond with their therapist (Meier, 2023). Early formation of a therapeutic bond, however, can mediate these early dropout rates, as shown in Anderson et al. (2018). In this naturalistic study of clients participating in individual, couple and family, or high conflict coparenting therapy, 20% discontinued therapy within the first three sessions; however, formation of an early therapeutic alliance played a significant role in client retention after these three sessions. This demonstrates that the therapeutic alliance is something that clients value in therapy, and that clients will be willing to attend therapy longer if there are higher levels of therapeutic alliance early in therapy.

The current study used a DD model (Smith & Hantula, 2008; Tesch & Sanfey, 2008) to identify therapy clients’ tendency to choose between shorter and longer therapy programs that offer differing levels of alliances with their therapist. Specifically, this study used DD to calculate the point in the therapeutic alliance at which clients are willing to go to therapy for longer, despite options for a shorter therapy program with a lower therapeutic bond. DD is the tendency of individuals to favor smaller, immediate rewards over larger rewards that come after a delay (Berns et al., 2007; Kirby et al., 1999; as cited in Lempert et al., 2012), suggesting that the subjective value of rewards decrease over time. For example, a person may subjectively favor $50 today over $75 one month from now, in which

case the person subjectively deems the larger reward of $75 as less valuable because of the time they must wait to receive the reward (Swift & Callahan, 2009). Although several methods for calculating DD have been proposed (Smith & Hantula, 2008; Tesch & Sanfey, 2008), the overall method of assessing a participant’s degree of discounting (i.e., indifference point) is by identifying the moment when the person considered the smaller, immediate reward equivalent to the larger, delayed reward (Chadwell et al., 2019; Swift & Callahan, 2009). DD assessments typically involve systematically manipulating the value of rewards (or the therapeutic bond in this study) until a participant no longer indicates a preference for one reward over another (Chadwell et al., 2019; Swift & Callahan, 2009). Extrapolating from the above example, an individual may choose a delayed reward over the $50 immediate reward if the delayed reward is raised from $75 to $100. In this case, because the person chose the immediate reward when the delayed reward was only $75 but switched to the delayed reward when it increased to $100, the person’s indifference point would fall in between $75 and $100. In other words, at some point between $75 and $100, the subjective value of the delayed reward is equal to the value of the immediate reward. The rates that people discount future rewards have varied across individuals and contexts, so it is important to understand factors that may influence people’s varied discounting rates. DD has been widely used in psychological and economic research to study decision­making behaviors, specifically in studies related to self­control and impulsivity in decision making (da Matta et al., 2011). Although DD has been used in various ways, it has emerged as an important measure for psychotherapy researchers. For example, Swift and Callahan (2009, 2010a) used DD to assess certain client preferences (such as the client or therapist talking more within sessions), client expectancies, and client termination. Furthermore, Chadwell et al. (2019) uses DD to assess client’s preferences around treatment effectiveness and therapist process characteristics. DD is beneficial when looking at client preferences because oftentimes subjective values can be assigned to these preferences. For example, Swift and Callahan (2010) tested client preferences by asking participants to choose between a treatment that has a 70% recovery rate that is conducted by a therapist with few years of experience, and a treatment that has a 10% recovery rate that is conducted by a therapist with many years of experience. They then increased the 10% efficacy rate by 10% until the participant switched over to treatment with a therapist with many years of experience. This study found that clients were willing to discount a significant amount of treatment efficacy to ensure that their therapist would have

a greater level of experience. In terms of other measures, participants also discounted treatment efficacy to ensure a satisfactory therapeutic relationship, an empathetic and accepting therapist, and therapy sessions dominated by the client talking.

This study used similar measures of DD, but used client preferences for therapeutic alliance and therapy length instead of treatment efficacy and therapist characteristics for two sets of study hypotheses below (1a, 1b, 1c, 2a, 2b, and 2c)

Hypothesis 1a and 1b predicted that, when offered a short therapy duration of treatment with an unbonded or neutral therapeutic bond, respectively, participants would eventually switch to the longer therapy to pursue a stronger bond with their therapist. This makes sense, because in the DD paradigm, people tend to choose the lower, more immediate bond until the delayed, higher reward is just as favorable, at which point they switch to the delayed reward. Hypothesis 1c was also based on the delayed discounting framework, predicting that, when given the option of shorter therapy with the highest bonded therapist possible, people will always prefer this therapy over a longer therapy with a lower bonded therapist. This makes sense, because in the DD paradigm, when a person is offered an immediate reward that is higher than delayed reward, they tend to choose the large immediate reward because the delay only decreases the already low reward.

Hypotheses 2a, 2b, and 2c looked at differences between clients’ preferences when they switched to an 8 ­ week and to a 12 ­ week program. Hypotheses 2a and 2b predicted that participants would require a significantly higher bond to switch to the 12­week therapy program than they required to switch to an 8­week therapy program from a 4­week program with unbonded therapeutic bonds and neutral therapeutic bonds, respectively. This aligns with the DD paradigm because switching from a 4­week program to a 12­week program involves more delay than switching from a 4­week program to an 8­week program, and therefore the therapeutic alliance value when switching to a 12­week program will be subjectively discounted at a higher rate than switching to an 8­week program. It follows that people will stay in the 4­week therapy program for longer when given the choice of the 12­week program than the 8 ­ week program, as the delayed rewards mean less. Finally, Hypothesis 2c predicted that there would be no significant difference between participants’ indifferent points when switching to the 8­ and 12­week conditions because they would always choose the shorter therapy program with the highest level of therapeutic alliance available over the longer therapy with a less bonded therapist. This makes sense

Zwolinski

because, according to the DD paradigm, people tend to always want a larger immediate reward, and therefore would never choose the longer therapy in either case. Data from this research can inform therapists of what levels of therapeutic relationships are important to clients who are ready to attend therapy and make changes in their lifestyles to improve their mental health, as well as how these relationships affect clients’ willingness to continue therapy for longer periods of time. This study was guided by the Prochaska’s Stages of Change Model (Prochaska & DiClemente, 1983), as participants were screened to be either currently attending therapy or waiting to attend therapy to ensure that they were in the Action and/or Maintenance stages of the model and ready to make psychological changes in their life. It is important to study this group of participants because this self­motivation could play a role in how much therapeutic alliance is needed for this group to remain in therapy for longer.

Methods

Participants

A total of 115 participants who resided in the United States expressed an interest in participating in the study. Participants were eliminated from the final analysis sample for several reasons including: technical time out issue for a participant resulting in two sets of data (n = 1), substantial missing data (n = 3), or participant random clicking during the survey (e.g., all scores were unrelated, which was observed because of the continuous nature of the DD questionnaires; n = 6). Of the final participant pool of 105 participants, a total of 79 identified as women, 26 identified as men, 8 identified as nonbinary, and 1 identified as other. For sexual orientation, 69 participants identified as heterosexual/straight, 12 identified as gay/lesbian, 32 identified as other, and 1 reported not knowing which group they identified with. The participants’ average age was 34.92 years (SD = 10.87) with a range of 20 to 75 years (N = 112). In terms of race, 92 participants identified as White, 11 identified as Black or African American, 5 identified as American Indian or Alaska Native, 2 identified as Asian Indian, 1 identified as Chinese, 1 identified as Vietnamese, and 2 identified as other Asian. One hundred one participants did not identify with Hispanic, Latino/a, or Spanish origin, while 6 identified with Mexican, Mexican American, and/or Chicano/a, 2 identified as Puerto Rican, 1 identified as Cuban, and 3 identified with another Hispanic, Latino/a, or Spanish origin. Participant employment status included 63 participants working as paid employees, 15 working (self ­ employed), 2 not working due to a temporary layoff from a job, 15 not working but looking for work,

2 not working due to retirement, 9 not working due to a disability, and 7 not working for other reasons, with 1 participant stating that they were “working on their mental health until they were able to work.” In terms of marital status, 67 participants were never married, 32 participants were married, 3 participants were widowed, 11 were divorced, and 1 was separated. Other participant demographic variables included education, with 1 participant having lower than a high school degree, 15 participants having only graduated high school, 26 participants having some college but no degree, 13 participants having an associate’s college degree (2 years), 38 participants having a 4­year bachelor’s degree, 17 participants having a master’s degree, 1 participant having a doctoral degree, and 3 participants having a professional degree (JD, MD, etc). Participants’ total household income for the last 12 months before taxes consisted of 19 participants earning less than $25,000, 30 participants earning in between $25,000 and $49,999, 19 participants earning in between $50,000 and $74,999, 16 participants earning between $75,000 and $99,999, 14 participants earning between $100,000 and $149,999, 8 participants earning between $150,000 and $199,999, 3 participants earning between $200,000 and $249,999, and 2 participants earning $250,000 or more. Finally, 12 participants noted that they did not have health insurance, while 102 did have health insurance. Of the participants who noted that they did have health insurance, 3 participants claimed that it did not offer mental health coverage, while 95 participants claimed that they did have mental health coverage through their health insurance.

Procedure

Following IRB approval from the University of San Diego, eligible participants were recruited via Prolific, a web ­ based data collection platform that allows researchers to recruit participants for online research studies. To be included in the study, participants had to be at least 18 years old, reside in the United States, and currently be receiving or waiting to receive treatment for symptoms of a mental health condition (i.e., indicative of being in the Action and Maintenance stages of readiness). Participants were offered $6.00 to complete the online survey using Qualtrics. Participants were told that the study would take approximately 30 minutes to complete, although the average amount of time participants took to complete the study was 15 minutes and 31 seconds. After completing a consent form, participants completed a series of questionnaires that assessed participants’ validation (i.e., CAPTCHA), background information, current mental health functioning, general health­seeking behaviors, path

to treatment, attitudes towards seeking professional mental health, and preferences for a therapist, as well as questions that assess how long clients are willing to stay in therapy in the face of differing therapist interpersonal traits and differing strengths of therapeutic alliance in therapy. Finally, participants completed questions that measured attention and comprehension. For purposes of this article, in addition to study validation, attention measures, and comprehension measures, only the study questionnaires described below were evaluated. Data from this study were part of a larger study that included additional questionnaires noted above proposed to be related to alliance and client retention.

Assessments

To assess participant background information, participants were asked various questions including age, gender, race, ethnicity, total household income, current student enrollment status, employment status, marital status, military background, and access to health insurance.

To study client preferences for therapeutic alliance and length of therapy, this study used vignettes created by the principal investigator and co principal investigator modeled after Swift and Callahan’s (2009) DD framework. In Vignettes Series 1a (weeks 4 and 8), participants read vignettes and then responded to indicate their preference for length of therapy and therapeutic alliance, as shown in Appendix A below. Descriptions utilized terminology from The Working Alliance Inventory­Short Revised (Paap & Dijkstra, 2017) that were provided for each of the anchors for bonding.

Then, participants responded to 10 questions that asked them to rate preferences for a 4­week treatment with a 1/10 therapeutic bond or 8­week treatment with varying levels of therapeutic bond (1–10/10) using the scale noted above. The second vignette followed the same pattern, with 10 questions asking participants to choose between a 4­week treatment with a neutral bond (5/10) with their therapist or an 8­week treatment with varying levels of therapeutic bond (1–10/10). The third vignette also follows this pattern, with 10 questions that offer a strong therapeutic bond (10/10) for the 4­week program and asks participants if they would rather this or an 8­week treatment with varying levels of therapeutic bond (1–10/10).

The same pattern was used for the fourth, fifth, and sixth vignettes for Vignettes Series 1b (weeks 4 and 12), except the vignettes were now comparing weeks 4 and 12 (week 8 above was replaced with 12 here). Weeks 4, 8, and 12 were chosen as anchors because research has indicated that, compared to week 4 of treatment, people tend to show increases in well­being (and related anxiety) following cognitive behavioral therapy at week 8 and again at week 12 (Gallagher et al., 2020).

Breaux and Zwolinski | Therapeutic Alliance and Client Retention

In Vignettes Series 1a (weeks 4 and 8) and Vignettes Series 1b (weeks 4 and 12), the DD measure was used to calculate the indifference point, or the point at which participants switched from the 4­week therapy to a longer therapy with different levels of therapeutic alliance. For the sake of this study, the indifference point was calculated by averaging the points that the participant switched preferences between a pair of comparison points (Odum et al., 2011), mirroring Swift and Callahan’s (2009) manner of DD calculation in psychotherapy research. For example, say a participant in this study chose to remain in the 4­week therapy with a neutral bond (5/10) with their therapist until the longer, 8­week therapy offered a 7/10 bond with their therapist. In this case, the person made the switch to the longer therapy when it could offer in between a 6/10 and a 7/10 level bond. Their indifference point would therefore be 6.5 (the average of 6 and 7), indicating that the person would rather stay in a shorter, 4­week therapy with a neutral therapist (5/10) until the longer, 8­week therapy offered a therapeutic bond of 6.5/10 (see Appendix B). A higher indifference point indicates that the person is more willing to discount the therapeutic relationship in therapy, and they require a higher therapeutic bond to justify switching to a longer therapy program. A lower indifference point indicates that people discount less of the therapeutic bond for therapy length, and they do not require as much of a therapeutic bond to switch to a longer therapy program. Indifference points for each participant were created for each of the 6 conditions (1/10 for 4 weeks, __/10 for 8 weeks; 5/10 for 4 weeks, __/10 for 8 weeks; 10/10 for 4 weeks, __/10 for 8 weeks; 1/10 for 4 weeks, __/10 for 12 weeks; 5/10 for 4 weeks, __/10 for 12 weeks; 10/10 for 4 weeks, __/10 for 12 weeks) in order to run analysis for Hypotheses 1 and 2.

Results

Hypothesis 1: Client Preferences for Therapeutic Alliance and Therapy Length at the Unbonded, Neutral, and Bonded Bond Levels

Three sub­hypotheses for Hypothesis 1 were formed to examine client’s preferences for therapeutic bond and length of therapy through a measure of DD. Before testing these hypotheses, data assumptions were evaluated. The data were not normally distributed for DD values for weeks 4 to 12 by bond, despite attempts to normalize the data using log transformations. Therefore, Wilcoxon signed­rank tests were conducted for all three levels of therapeutic bond. See Figure 1.

Hypothesis 1a: Unbonded

A single sample Wilcoxon signed­rank test determined that the median change in indifference point when

subjects reported on willingness to continue from 4­ to 8­week treatment (Mdn = 4.50) was significantly different than the hypothetical value for the unbonded bond (Mdn = 1.00), Z = 8.81, p < .001, N = 102. Similarly, a second single sample Wilcoxon signed ­ rank test determined that the median change in indifference point when subjects reported on willingness to continue from 4 ­ to 12 ­ week treatment ( Mdn = 5.50) was significantly different than the hypothetical value for the unbonded therapeutic relationship (Mdn = 1.00), Z = 8.85, p < .001, N = 104.

Hypothesis 1b: Neutral Bond

A single sample Wilcoxon signed­rank test determined that the median change in indifference point when subjects reported on willingness to continue from 4­ to 8­week treatment (Mdn = 5.50) was significantly different than the hypothetical value for the neutral bond (Mdn = 5.00), Z = 4.15, p < .001, N = 104. Similarly, another single sample Wilcoxon signed ­ rank test determined that the median change in indifference point when subjects reported on willingness to continue from 4­ to 12­week treatment (Mdn = 6.00) was significantly different than the hypothetical value for the neutral bond (Mdn = 5.00), Z = 6.72, p < .001, N = 104.

Hypothesis 1c: Bonded

A single sample Wilcoxon signed­rank test determined that the median change in indifference point when subjects reported on willingness to continue from

Therapeutic Bond Level and Willingness to Continue Treatment Across Time

FIGURE 1

4­ to 8­week treatment (Mdn = 8.50) was significantly different than the hypothetical value for the “bonded” bond ( Mdn = 10.00), Z = ­ 7.67, p < .001, N = 104. Similarly, a single sample Wilcoxon signedrank test determined that the median change in indifference point when subjects reported on willingness to continue from 4 to 12­week treatment ( Mdn = 8.50) was significantly different than the hypothetical value for the bonded bond (Mdn = 10.00), Z = ­7.67, p < .001, N = 104.

Hypothesis 2: How Different Therapy Program Lengths (8 vs 12 weeks) Affect Alliance Preferences at the Unbonded, Neutral, and Bonded Bond Levels

For Hypothesis 2, three subhypotheses were formed to assess how people’s preferences for therapeutic alliance change when they are offered therapies of different lengths. Before testing these hypotheses, data assumptions were evaluated. The data were not normally distributed for DD values for weeks 4 to 8 and for weeks 8 to 12, despite attempts to normalize the data using log transformations. Therefore, Wilcoxon signed­rank tests were conducted for all three levels of therapeutic bond. See Figure 1.

Hypothesis 2a: Unbonded

A total of 101 participants were analyzed to understand the extent of DD indifference points at an unbonded bond for willingness to continue therapy from 4 to 8 weeks, vs. 4 to 12 weeks. Data refers to indifference point medians unless otherwise stated. The unbonded elicited an increase in DD in the willingness to continue therapy from 4 to 12 weeks compared to the participants moving from 4 to 8 weeks for 61 participants, whereas 30 participants reported no change in willingness to continue therapy, and 10 participants were unwilling to continue treatment beyond 8 weeks. A Wilcoxon signed­rank test determined that there was a statistically significant median decrease in indifference point when subjects reported on willingness to continue from 4­ to 12­week treatment (Mdn = 5.5) compared to willingness to continue from 4­ to 8­week treatment (Mdn = 4.5), Z = ­5.79, p < .001.

Hypothesis 2b: Neutral Bond

A total of 104 participants were analyzed to understand the extent of DD indifference points at a neutral bond for willingness to continue therapy from 4 to 8 weeks, vs. 4 to 12 weeks. Data are indifference point medians unless otherwise stated. The neutral bond elicited an increase in DD in the willingness to continue therapy from 4 to 12 weeks compared to the participants moving from 4 to 8 weeks for 47 participants, whereas 46 participants reported no change in willingness to

continue therapy, and 11 participants were unwilling to continue treatment beyond 8 weeks. A Wilcoxon signed­rank test determined that there was a statistically significant median increase in indifference point when subjects reported on willingness to continue from 4 to 12­week treatment (Mdn = 6.0) compared to willingness to continue from 4 to 8­week treatment (Mdn = 5.5), Z = ­5.04, p < .001.

Hypothesis 2c: Bonded

A total of 104 participants were analyzed to understand the extent of DD indifference points at a bonded bond for willingness to continue therapy from 4 to 8 weeks, vs. 4 to 12 weeks. Data are indifference point medians unless otherwise stated. The high bond elicited an increase in DD in the willingness to continue therapy from 4 to 12 weeks compared to the participants moving from 4 to 8 weeks for 21 participants, whereas 54 participants reported no change in willingness to continue therapy, and 29 participants were unwilling to continue treatment beyond 8 weeks. A Wilcoxon signedrank test determined that there was no statistically significant median change in indifference point when subjects reported on willingness to continue from 4 ­ to 12 ­ week treatment ( Mdn = 8.50) compared to willingness to continue from 4­ to 8­week treatment (Mdn = 8.50), Z = ­1.65, p = .10.

Discussion

The purpose of this study was to assess the extent to which the level of therapeutic bond or alliance is related to preferences for time spent in therapy. This study used DD and the Prochaska and Diclemente’s Stages of Change Model (Prochaska & DiClemente, 1983) to investigate the point (i.e. indifference point) at which therapeutically­motivated clients chose an effective, long­duration therapy that offered a higher therapeutic alliance as opposed to an equally effective, short­duration therapy that offered a lower therapeutic alliance. More specific summaries and implications about each two sets of hypotheses are described below.

Hypothesis 1a: Unbonded

Hypothesis 1a predicted that, when offered a 4­week therapy with an unbonded therapist or a longer therapy (8 or 12 weeks) with an increasingly higher bond with their therapist, people in a short therapy with an unbonded therapist would switch to the longer therapy if it offered a significantly higher bond. As predicted, people’s indifference points were significantly larger than 1/10 for both the 8­week and 12­week switches, with indifference points of 4.5 and 5.5 respectively.

Breaux and Zwolinski | Therapeutic Alliance and Client Retention

This means that people were willing to stay in a short, 4­week therapy with an unbonded therapist until the bond increases to a neutral bond, at which point they were willing to go to therapy for a longer period of time. The fact that participants wanted to switch from a short therapy with an unbonded therapist to a longer therapy when the therapeutic bond was neutral shows that clients value therapeutic alliance in therapy to a certain degree, and it did affect their preference for retention in therapy as supported by previous literature (Meier, 2024; Sijercic et al., 2021).

Hypothesis 1b: Neutral Bond

Hypothesis 1b predicted that, when offered a 4­week therapy with a neutral bonded therapist (5/10) or a longer therapy with an increasingly higher bond with their therapist (6–10/10; via DD), people would switch to the longer therapy (8 or 12 weeks) at a bond significantly larger than a neutral bond (5/10) in order to pursue a stronger bond with their therapist. This hypothesis was supported when participants were asked to switch to both the 8 ­ and 12 ­ week therapy programs, with indifference points being 5.5 and 6.0 respectively. This means that people are willing to stay in a short, 4­week therapy with a neutral therapist until a longer therapy offers a slightly above­neutral therapeutic alliance, at which point they are willing to switch to a longer therapy program. This, combined with Hypothesis 1a, suggests that people solely require a neutral bonded therapist or slightly above a neutral bonded therapist to justify attending therapy for a longer period of time.

These results suggest that therapist alliance does play a role in client retention in therapy; however, the DD technique reveals that people who are motivated to attend therapy only need a slightly above­neutral bond to justify attending therapy for longer. Motivated clients having this relatively low indifference point is supported by a study by Brocato (2004), which found that, in prisoners attending therapy, people’s motivations for change were a higher predictor of therapy retention than the therapeutic alliance. This brings us back to this study’s application of the Stages of Change Model (Prochaska & DiClemente, 1983), suggesting that this study’s population may not require as strong of a therapeutic alliance to remain in therapy for longer because they are already self ­ motivated (i.e., in the Action and Maintenance stages) to improve. In all, these results suggest that the therapeutic alliance does play a significant role in retention, but only to a certain degree—people who are motivated to attend therapy really only need slightly above neutral alliance to justify switching to a longer therapy.

Hypothesis 1c: Bonded

Hypothesis 1c predicted that, when given the option of a 4 ­ week therapy with a highly bonded therapist (10/10), people will always prefer this therapy over a longer therapy (8 or 12 weeks) with a less bonded therapist (1–9/10), and there will therefore be no significant change in indifference point. These results were not supported for 8 weeks and 12 weeks (with indifference points being 8.5 and 8.5 respectively), which is particularly interesting because this went against our initial hypothesis and normal human tendencies in DD to choose an immediate reward that is higher over a delayed reward that is lower. The results suggest that clients preferred a longer therapy and/or ability to build a connection with their therapist over time over a short therapy with the highest possible bond with their therapist. In other words, clients could be willing to discount a little bit of the therapeutic relationship so that they attend therapy longer, either because they prefer a longer therapy, or so that they can build the therapeutic relationship over time. This is supported in Prusiński (2024), who found that, for adults with adaptation disorders, the therapeutic alliance increased by a stable linear trend over time, and that the therapeutic alliance was correlated to positive therapeutic outcomes. Based on these findings, clients may associate longer therapy sessions with a higher therapeutic bond and better therapeutic outcomes. Additionally, client willingness to discount some of the therapeutic alliance to attend a longer therapy program is supported by Bose et al. (2023), who found that increased session attendance is significant in enhancing therapeutic outcomes, while building an early, strong therapeutic alliance does not.

Going off of these findings, it can be concluded that clients may feel that a longer therapy program will help them recover more than the highest therapeutic alliance possible could. Although participants discounted a shorter therapy program with the highest bond possible, participants still wanted a relatively high therapeutic bond with their therapist in order to switch to a longer therapy (8.5) as opposed to the neutral/slightly above neutral bond (5–6/10) that was observed with Hypotheses 1a and 1b. This result could be supported by previous research findings that developing a therapeutic alliance early in therapy will increase the sessions that clients attend (Meier, 2024), and even that overall ratings of therapeutic alliance (as opposed to initial alliance, late alliance, and change in alliance over treatment) is a significant predictor of client dropout in a cognitive processing therapy therapy for clients with PTSD (Sijercic et al., 2021), as clients prefer the longer therapy with a “bonded” therapeutic relationship over the short therapy with a “bonded” therapeutic relationship.

Hypothesis 2a: Unbonded

Hypothesis 2a predicted that people would want a significantly higher bond to switch to a 12­week therapy program than the bond it would take them to switch to an 8­week therapy program when they were in a 4­week therapy with an unbonded therapist. The results for Hypothesis 2a were supported, as the indifference points for switching to 8 weeks (4.5) and 12 weeks (5.5) were significantly different. This means that people discounted more of the therapeutic relationship when given the option of the 12­week program, more preferring to stay in a short therapy with an unbonded therapist than people given the option of an 8­week program. This suggests that therapeutic alliance does play a significant role in how long people are willing to go to therapy when the bond with their therapist is “unbonded.” This is supported by previous findings that the overall therapeutic alliance does affect client’s retention in therapy, as found in Meier (2024) and Sijercic et al. (2021), both who compared the therapeutic alliance within therapy with the participant’s dropout rate within therapy. Although this study had similar findings, this study specifically analyzed the point in the therapeutic relationship clients are willing to go to therapy for longer periods of time. Specifically, this finding showed that, although the point in which participants switched to an 8­week program and the point in which they switched to a 12­week program were significantly different, it was only a 1­bond point difference, and both conditions switched when the bond level was around neutral. This shows that people do need a higher bond level to switch to a longer therapy session (8 weeks vs 12 weeks) from a short therapy with an unbonded therapist, but both are willing to switch around the neutral bond level (4.5 vs 5.5).

Hypothesis 2b: Neutral Bond

Hypothesis 2b predicted that people would want a significantly higher bond to switch to a 12­week therapy program than the bond it would take them to switch to an 8­week therapy program. This hypothesis was supported, as the indifference point for switching to an 8­week (5.50) or a 12­week (6.00) therapy was significantly different. This suggests that clients are willing to go to a therapy with a neutral bonded therapist for 8 weeks, but they require a more bonded relationship with their therapist to justify going to therapy for 12 weeks. This suggests that therapeutic alliance does play a significant role in how long people are willing to go to therapy when the bond with their therapist is neutral. This is supported by previous findings that therapeutic alliance does affect client’s retention in therapy, as found in Meier (2024) and Sijercic et al. (2021); these studies, however, compared the therapeutic alliance within therapy with the participant’s

dropout rate within therapy, while this study assessed client preferences for the point in the therapeutic relationship they were willing to go to therapy for longer. This was done by finding the median indifference point at which participants switched to the 8­week and the 12­week therapy program. Specifically, although the difference was significant, there was only a 0.50 point difference in therapeutic bond between when people were willing to switch to an 8­week program than a 12­week program, and both conditions switched when the bond level was slightly above neutral. This shows that people do need a higher bond level to switch to a longer therapy session (8 weeks vs 12 weeks) from a short therapy with a neutral therapist, but both are willing to switch when the therapeutic alliance is slightly above neutral bond level (5.50 vs. 6.00).

Hypothesis 2c: Bonded

Hypothesis 2c predicted that, when participants are offered a 4 ­ week program with the highest bonded therapeutic alliance possible (10/10), there will be an insignificant difference between people switching to 8­ and 12­week programs because people will always want the higher, more immediate reward. The results supported this hypothesis, showing that there was no significant change in indifference point between 8 and 12 weeks. This suggests that clients did not prefer a higher bond for 12 weeks as opposed to 8 weeks, suggesting that the additional 4 weeks in therapy does not matter for people who are therapeutically motivated as long as the bond is relatively high/bonded. This shows that therapeutic alliance affects client retention in therapy, as shown by Meier (2024) and Sijercic et al. (2021), but only up until a certain point. Once clients perceive therapeutic alliance to be relatively high, it may not play a huge role in whether a client chooses to terminate therapy or not.

Limitations

This study included limitations that might have impacted the findings. One limitation included this study’s limited time points of 8 and 12 weeks, which prevented an analysis using Area Under the Curve (AUC). As demonstrated in Myerson et al. (2001), the AUC measure consists of calculating the area under the empirical discounting function at multiple points of delay (more than the two points in this study), which is a commonly used measure of calculating the degree of discounting. Although calculating the median indifference point is a valid form of DD measurement, as seen in Swift and Callahan (2009, 2010a) and Chadwell (2019), future research could conduct the current study again with more data points in order to run an AUC analysis. This AUC analysis would then yield a single number between 0 and 1 to characterize the extent to which participants

discounted the therapeutic alliance to attend shorter or longer therapy sessions (with numbers closer to 1 suggesting maximum discounting and numbers closer to 0 suggesting minimum discounting; Odum, 2011). Although we would not be able to determine the point in the therapeutic alliance that clients actually switched therapy programs (i.e., indifference point), this form of analysis would allow us to see the data in a new way, yielding the rate in which participants discounted the therapeutic alliance for different therapy lengths. Furthermore, adding more time points would yield a better understanding of people’s decisions around therapy, as different lengths of therapy may alter people’s decisions around retention.

Another limitation included the subjectivity of the Therapeutic Alliance scale included in the vignettes, as there were no descriptions for numbers on the scale in between the main values of 1/10, 5/10, or 10/10. People’s different perceptions of the numbers in between could have skewed the results, which should be taken into consideration in future DD studies that assign values to a scale. Future research that uses DD in this manner could define every value on the scale so that it is less up to participant interpretation. Finally, another limitation was the participant screening as offered by Prolific, as it included all people “currently receiving or waiting to receive treatment for symptoms of a mental health condition.” These two groups of people could have different preferences when it comes to therapy length and therapeutic alliance, which could have skewed the data as well. Future research could look at these preferences with just one of these groups, or even see how these groups’ preferences differ.

Another limitation of this study included assumptions made about participants’ motivation to participate in therapy due to their current state of “receiving therapy” or “waiting to receive therapy.” Because clients in these groups might have been forced, coerced, or encouraged to seek treatment, future studies should assess participants on their motivation rather than assuming motivation. Additionally, although therapy durations of 4, 8, and 12 were based on when clients showed improvements in anxiety in Gallagher et al. (2020), the baseline of 4 weeks may be unrealistically short, especially for participants who had already been in therapy for more than 4 weeks. Future research should assess participants on their expectations for therapy duration. Finally, the polarity of the rating scale, with the “unbonded” side meaning that the therapist does not respect or like them, might have pushed clients to the “close to neutral” ground. It is important to consider that this aversive “unbonded” label might have played a role in the findings.

Strengths

This study also included various strengths. First of all, this was one of the first studies to examine preferences for therapeutic alliance and therapy retention in clients who are in the Action and Maintenance stages of the Prochaska and Diclemente’s (1983) Stages of Change Model. For this reason, this study grants a unique perspective on client preferences and retention based on people who are ready to attend and stay in therapy, rather than a broad sample that includes people who may not be in the mindset of attending therapy at all. Furthermore, while other studies (Barber et al., 2001; Brocato, 2004; Levin et al., 2024; Meier et al., 2024; Sijercic et al., 2021) have looked at how therapeutic alliance directly affects dropout or therapy outcomes, this study was the first to weigh the levels of therapeutic relationships that clients want against the amount of time that clients want to attend therapy.

Implications

The results of this study indicate that clients are willing to go to therapy for longer when they have at least a moderate bond with their therapist, and that when clients do feel that they have a bonded therapeutic bond with their therapist, they would rather go therapy for a longer period of time than a shorter period of time (4 weeks as opposed to 8 and 12 weeks). This specific timeframe for therapy was specifically selected because of Gallager et al.’s (2020) findings that, in cognitive behavioral therapy for anxiety, people tend to show increases in well­being (and related anxiety) at week 8 and again at week 12 compared to week 4 of treatment, thus we assumed treatment would be comparably effective at this timeframe for this study. Because this study screened its participants to be in the Action and Maintenance stages of the Prochaska and Diclemente’s Stages of Change Model (and they therefore had self­motivation to make positive changes in their lifestyle to improve their mental health), this study highlights that therapeutic alliance may not be as important to clients in retention than their own self­motivation to remain in therapy (Brocato, 2004). This could also suggest that, when a therapeutic relationship is high, clients may prefer to attend the therapy for longer in order to maintain an ongoing relationship with their therapist. All of these findings are important for clinicians to consider when they are forming relationships with their clients, as previous literature has been mixed on whether therapeutic alliance affects clients’ retention in therapy or not.

Future Directions

Along with the suggestions made in the limitations paragraph above, there are several other future directions Breaux and Zwolinski

that researchers could take from this study. First of all, the lack of consistency in research findings on whether the client–therapist alliance plays a role in client retention in therapy or not suggests that further research should be done on this topic in general. For example, Meier et al. (2024) and Sijercic et al. (2021) found that the client therapist alliance does play a role in client retention, while Barber et al. (2001) and Brocato (2004) showed that there is no relation between the two. These inconsistencies may be due to various other factors that go into therapy attendance such as client self­motivation to attend therapy and client preferences for the type of therapy itself, as shown in Brocato (2004) and Barber et al. (2001). A study that takes client self­motivation, client preferences for type of therapy, and therapeutic alliance into account when it comes to client retention could give further insight into how these variables interact and influence client retention. In addition, researchers could also look at how individual factors such as age, gender, race, income, and other demographic factors may play a role in people’s preferences surrounding therapeutic alliance and length of therapy. For example, it could be hypothesized that females may have a larger preference for a strong bond with their therapist than males, and may be more willing to go to therapy for longer in order to pursue this bond. Also, in terms of income, it could be hypothesized that people with low incomes are more likely to discount the therapeutic bond than people with high incomes, choosing the shorter therapy with a less bonded therapist over the longer therapy with a more bonded therapist because of financial factors. Furthermore, it may be of interest to study how people’s current state of stress, depression, and anxiety play a role in how long they are willing to go to therapy and their preferences for a therapeutic alliance. Ultimately, an understanding of the individual client and client–therapist factors that are associated with client retention will result in better clinical outcomes for clients.

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Barber, J. P., Luborsky, L., Gallop, R., Crits-Christoph, P., Frank, A., Weiss, R. D., Thase, M. E., Connolly, M. B., Gladis, M., Foltz, C., & Siqueland, L. (2001). Therapeutic alliance as a predictor of outcome and retention in the National Institute on Drug Abuse Collaborative Cocaine Treatment Study. Journal of Consulting and Clinical Psychology, 69(1), 119–124. https://doi.org/10.1037//0022-006x.69.1.119

Bose, D., Pettit, J. W., Silk, J. S., Ladouceur, C. D., Olino, T. M., Forbes, E. E., Siegle, G. J., Dahl, R. E., Kendall, P. C., Ryan, N. D., & McMakin, D. L. (2023). Therapeutic alliance, attendance, and outcomes in youths receiving CBT or client-centered therapy for anxiety. Journal of Clinical Child and Adolescent Psychology, 1–11. https://doi.org/10.1080/15374416.2023.2261547

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Correspondence should be sent to Madeline M. Breaux, Department of Psychological Sciences, 5998 Alcala Park, San Diego, CA 92110. Email: mbreaux@sandiego.edu Breaux and Zwolinski |

5(3–4), 278–293. https://doi.org/10.1037/h0100889

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Author Note

Madeline M. Breaux https://orcid.org/0009­0001­9092­4316

Jennifer Zwolinski https://orcid.org/0000­0002­8239­0190

This project was funded by the University of San Diego (USD) Office of Undergraduate Research Beginning Undergraduate Research Summer Training (BURST) Grant and the USD Associated Student Government Undergraduate Academic Research Grant given to the first author.

APPENDIX A

Vignette Based on the Delayed Discounting Framework to Set Up Preference Questions for Therapeutic Alliance and Length of Therapy

Instructions:

For each question, imagine you have been struggling with anxiety in your everyday life. You will be given the option of choosing a treatment that lasts 4 weeks with a therapist you would rate your bond with as a 10/10 (see scale below), or a treatment that lasts 8 weeks with a therapist you would rate your bond with as a __/10 (see scale below). Keep in mind that both therapies have high recovery rates, and that you are estimated to make the same amount of progress by the end of both. Please base your rating using the scale below.

1 = You do not feel bonded with your therapist. You do not believe that your therapist likes you, nor do you like your therapist. You do not feel as though you and your therapist work together to solve your problem nor do you have similar goals for the therapy. Overall, you do not feel like your therapist respects you.

5 = You feel neutral towards your therapist. You do not think your therapist likes or dislikes you, and you do not necessarily like or dislike your therapist. You kind of feel like you and your therapist work together to solve your problem and have similar goals, but you aren’t really sure. You are unable to tell if your therapist respects you or not.

10 = You feel very bonded with your therapist. You believe your therapist likes you, and you like your therapist. You feel as though you and your therapist work together to solve your problem and that you share similar goals for the therapy. You feel as though your therapist respects you.

APPENDIX B

Delayed Discounting Preference Questions Following Vignette

This Participant chose to remain in the 4-week therapy with a neutral bond (5/10) with their therapist until the longer, 8-week therapy offered a 7/10 bond with their therapist. In this case, the person made the switch to the longer therapy when it could offer in between a 6/10 and a 7/10 level bond. Their indifference point would therefore be 6.5 (the average of 6 and 7), indicating that the person would rather stay in a shorter, 4-week therapy with a neutral therapist (5/10) until the longer, 8-week therapy offered a therapeutic bond of 6.5/10.

Which would you prefer?

 4 week treatment with a therapist you would rate your bond with as 5/10

 8 week treatment with a therapist you would rate your bond with as a 1/10

Which would you prefer?

 4 week treatment with a therapist you would rate your bond with as 5/10

 8 week treatment with a therapist you would rate your bond with as a 2/10

Which would you prefer?

 4 week treatment with a therapist you would rate your bond with as 5/10

 8 week treatment with a therapist you would rate your bond with as a 3/10

Which would you prefer?

 4 week treatment with a therapist you would rate your bond with as 5/10

 8 week treatment with a therapist you would rate your bond with as a 4/10

Which would you prefer?

 4 week treatment with a therapist you would rate your bond with as 5/10

 8 week treatment with a therapist you would rate your bond with as a 5/10

Which would you prefer?

 4 week treatment with a therapist you would rate your bond with as 5/10

 8 week treatment with a therapist you would rate your bond with as a 6/10

Which would you prefer?

 4 week treatment with a therapist you would rate your bond with as 5/10

 8 week treatment with a therapist you would rate your bond with as a 7/10

Which would you prefer?

 4 week treatment with a therapist you would rate your bond with as 5/10

 8 week treatment with a therapist you would rate your bond with as a 8/10

Which would you prefer?

 4 week treatment with a therapist you would rate your bond with as 5/10

 8 week treatment with a therapist you would rate your bond with as a 9/10

Which would you prefer?

 4 week treatment with a therapist you would rate your bond with as 5/10

 8 week treatment with a therapist you would rate your bond with as a 10/10

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