NYU OPUS Vol. VIII Issue II | Fall 2017

The Online Publication of Undergraduate Studies was initiated in 2010 by undergraduate students in the Department of Applied Psychology, NYU Steinhardt. The ideas and opinions contained in this publication solely reflect those of the authors and not New York University. All work is licensed under the Creative Commons Attribution Noncommercial No Derivative Works License.

To view a copy of this license, visit http://creativecommons.org 2

OPUS

Online Publication of Undergraduate Studies Volume VIII Issue II | Fall 2017 Editors-in-Chief Julius A. Utama Elysha Clark-Whitney

Layout & Design Director Sophia Meifang Wang

Faculty Mentor Dr. Adina R. Schick

Programming & Communications Director Alyce Cho

Special Thanks NYU Steinhardt Department of Applied Psychology Dr. Gigliana Melzi Judson Simmons Kevin Jiang

Staff Writers Samantha Valley Contributing Writers Ali Swoish Christina Ducat Peter Goldie

3

C O N T E N T S 4

5 Letter From the Editors

8

Effects of Improvisational Music Therapy on Children with Autism Spectrum Disorder

Ali Swoish

11

Post-Treatment Employability Among Recovered Heroin Addicts: The Role of Agonist Therapies

Samantha Valley

13

Overt and Covert Discrimination Against the LGBT Community

Peter Goldie

17 Female Youth’s Dress in the Courtroom: Implications for Judicial Sentencing Severity

Christina Ducat

20

Teachers’ Responses to Disruptive Behavior in Ethnically Diverse Early-Childhood Classrooms

30 Biographies

Elysha Clark-Whitney & Julius A. Utama

Letter From the Editors

New York University’s Applied Psychology Online Publication of Undergraduate Studies, also known as OPUS, was established in 2009. OPUS provides Applied Psychology undergraduate students with a forum for sharing their independent work. This publication is entirely written, edited, and designed by Applied Psychology undergraduates, and is one of the only undergraduate psychology journals in the United States.

The themes of the Fall 2017 issue reflect the diverse clinical and research interests of our contributing writers, and demonstrate a desire to understand the nuances of psychological phenomena in order to improve the lives of a range of groups, thus embodying the ethos of Applied Psychology. First, our writers review research surrounding innovative therapies for at-risk populations: Ali Swoish investigates how improvisational music therapy can improve the social skills of children with Autism Spectrum Disorder, while Samantha Valley explores how agonist therapies can both support and hinder the post-treatment employability of recovered heroin addicts.

Another set of articles investigate experiences of discrimination among vulnerable populations in the United States.

Peter Goldie examines the nuanced difficulties faced by LGBT individuals, revealing the distinct effects of overt and covert forms of discrimination. Then, Christina Ducat outlines how judicial perceptions of female dress are associated with differential sentencing outcomes, and the role of cognitive processes such as defensive attribution in perpetuating a gendered court experience.

Our final article explores the role of adult-child interactions in the early childhood years. Julius Utama and Elysha Clark-Whitney qualitatively investigate how teachers’ responses to disruptive behaviors in ethnically diverse early-childhood classrooms differ depending on the type and severity of misbehavior.

We would like to thank our enthusiastic and talented writers for their scholarly contributions, as well as Sophia Meifang Wang and Alyce Cho, the OPUS administrative staff, for their hard work and commitment to the journal. We are also grateful to Dr. Gigliana Melzi, the Director of Undergraduate Studies in Applied Psychology, and Judson Simmons, the OPUS advisor, for their continuous support of OPUS. Finally, we would like to thank Dr. Adina R. Schick, our faculty mentor, for her guidance and dedication to OPUS, without which this issue would not be possible.

Best wishes and thank you for reading,

Julius A. Utama

Elysha Clark-Whitney 5

STAFF ARTICLE SUBMISS 6

S & IONS 7

Online Publication of Undergraduate Studies 2017, Volume 8, Issue 2

Improvisational Music Therapy for Children with ASD

Effects of Improvisational Music Therapy on Children with Autism Spectrum Disorder Ali Swoish

Autism Spectrum Disorder (ASD) is a complex neurodevelopmental disability that impacts cognitive, social, and sensory development (e.g., Crane, 2015; Kanner, 1943; LaGasse, 2017). Children diagnosed with ASD tend to withdraw from physical or social contact, and demonstrate a limited capacity to understand social cues (e.g., Edgerton, 1994; Kim, Wigram, & Gold, 2008; Lim, 2009). In fact, children with ASD have particular trouble developing joint attention and turn-taking behaviors -- two non-verbal communication skills integral in establishing and maintaining relationships (Crane, 2015; Harril & Jones, 2009; LaGasse, 2017; Spiro & Himberg, 2016). As early as six months (Pasiali, LaGasse & Penn, 2014; Spiro & Himberg, 2016; Wigram & Gold, 2006), children with ASD have difficulty exhibiting joint attention, or the ability to directly engage and share an experience with another individual through the use of eye contact, pointing, listening, and sustained concentration (Crane, 2015; Kim et al., 2008; Spiro & Himberg, 2016; Vaiouli et al., 2015). Likewise, children with ASD have difficulty understanding the reciprocal flow and social timing involved in turn-taking (i.e., an interaction in which two or more people initiate and respond to one another in a time-sensitive, backand-forth manner; Kim et al., 2008; LaGasse, 2016; Simpson & Keen, 2011; Spiro & Himberg, 2016). Given that joint attention and turn-taking are crucial for the later acquisition of more complex social skills such as sharing and symbolic play (BaronCohen, 1987; Spiro & Himberg, 2016; Wimpory et al., 1995), researchers have sought avenues to support the joint attention and turn-taking abilities of children on the Autism spectrum.

One such method that research has shown to be effective in engaging and socially stimulating children with ASD is Improvisational Music Therapy (e.g., Aigen, 1991; Carpente, 2014; Kim et al., 2008; Nordoff & Robbins, 1977).

In Improvisational Music Therapy, also known as Creative Music Therapy, therapists and clients use multiple instruments to create music and improvise with one another (Aigen, 2001; Nordoff & Robbins, 1977; Wigram & Gold, 2006). Research has acknowledged that the creative act of music making offers children with ASD an alternative form of self-expression, social engagement, and communication that increases their ability to initiate joint attention and turn-taking behaviors (Carpente, 2014; LaGasse, 2017; Spiro & Himberg, 2016; Wigram & Gold, 2006; Vaiouli, Grimmet, & Ruich, 2015). Given recent interest in music as an alternative method for supporting the development of social skills among children with ASD, this brief literature review addresses the following question: How does Improvisational 8 | Staff Articles & Submissions

Music Therapy affect the joint attention and turn-taking skills of children diagnosed with Autism Spectrum Disorder?

Joint Attention

Recent research suggests that Improvisational Music Therapy can support the acquisition of joint attention skills such as sharing eye contact and maintaining concentration on individuals or instruments for extended periods of time (Gold et al., 2006; Kim et al., 2008; Pasiali et al., 2014; Wigram & Gold, 2006). During Improvisational Music Therapy sessions, the child learns how to focus on one instrument or rhythmic pattern at a time while temporarily ignoring other instruments or patterns being played by the therapist (LaGasse, 2016; Pasiali et al., 2014; Vaiouli et al., 2015). The therapist supports the child’s ability to maintain sustained concentration by encouraging children to match the beat of the music, create their own rhythms, and to beat drums and play piano or guitar chords at a steady tempo for minutes at a time (Edgerton, 1994; Spiro & Himberg, 2016; Wigram & Gold, 2006). These tasks require children with ASD to engage in joint attention with the therapist by acknowledging them with their eyes and ears (Kim et al., 2008; Simpson & Keen, 2011; Spiro & Himberg, 2016). As eye contact, listening, and concentration become more frequent or elongated in Improvisational Music Therapy sessions, children with ASD begin to develop a predictable, structured understanding of how to listen and respond to musical stimuli (Kim et al., 2006; Spiro & Himberg, 2016; Vaiouli et al., 2015). This form of musical scaffolding grows in complexity as the sessions continue over time, allowing for the development of attention sharing, concentration, and active listening skills that generalize to real world social situations (Edgerton, 1994; Gold et al., 2006; Kim et al., 2008; Pasiali et al., 2014; Spiro & Himberg, 2016; Wigram & Gold, 2006).

In addition, research suggests that the Improvisational Music Therapy technique of musical attunement, in which the therapist matches the child’s expressions and emotions with the music during sessions, is associated with improvements in spatial awareness (Edgerton, 1994; Gold et al., 2006; Kim et al., 2008) -- a key component of joint attention. By listening to the child’s spontaneous musical input and matching their musical rhythm and melodies, Improvisational Music Therapists bring the child’s awareness outside of themselves and toward other people or instruments in the room (Kim et al., 2008; Wigram & Gold, 2006).

An increased sense of spatial awareness, in turn, allows the child to feel more comfortable in maintaining direct eye contact and

Online Publication of Undergraduate Studies 2017, Volume 8, Issue 2 concentration during a session (Edgerton, 1994; Kim et al., 2008). Therefore, by creating an interactive means of connection through music, Improvisational Music Therapy aids children with ASD in obtaining the joint attention behaviors necessary to focus, concentrate, and maintain eye contact throughout the session, and subsequently in other environments (Edgerton, 1994; Kim et al., 2008; Wigram & Gold, 2006).

Turn-taking

Research suggests that Improvisational Music Therapy can also support children’s acquisition of turn-taking skills, by providing rhythmic and structured musical activities that act as building blocks for understanding social timing and interpersonal communication (Harril & Jones, 2009; Spiro & Himberg, 2016; Vaiouli et al., 2015; Wimpory et al., 1995).

During music therapy sessions, therapists first guide children with ASD through repeated musical rhythms and phrases in order to create a structured format for communication (Kim et al., 2006; LaGasse, 2016). While playing instruments, the child learns to look towards the therapist and listen to the structured melodies and rhythms being created (Aigen, 2001; Gold et al., 2006; Kim et al., 2008; Spiro & Himberg, 2016). Over time, the repetition of listening, responding, and initiating behaviors during music therapy sessions provides the child with a predictable sense of which phrase will come next in the improvisation, wherein both child and therapist can pause and re-enter the phrase in a back and forth manner (Harril & Jones, 2009; Spiro, 2016; Wimpory et al., 1995).

As such, this improvised form of communication allows for practice in both receptive and expressive communication skills as the child gains the ability to intently listen to what the therapist is playing and thoughtfully respond in his or her own way (Simpson & Keen, 2011;Wigram & Gold, 2006). This backand-forth music making offers an opportunity for children with ASD to practice a musical conversation of listening, planning, and executing (Carpente, 2014; Spiro & Himberg, 2016; Wimpory et al., 1995; Vaiouli et al., 2015). These turn-taking skills often generalize to other environments, helping them to develop the interactive capacities necessary for play (Baron-Cohen, 1987; Harril & Jones, 2009; Wigram & Gold, 2006; Wimpory et al., 1995).

Conclusion

Overall, current research suggests that Improvisational Music Therapy supports the development of joint attention and turn-taking skills in children diagnosed with ASD, thus providing them with a better understanding of how to adequately interpret and actively respond to social stimuli. However, research has yet to delineate which therapist techniques are most effective in impacting the joint attention and turn-taking behaviors of children with ASD. Furthermore, the extant research has studied children on the Autism spectrum as an aggregate, without taking into consideration the deficits and level of functioning specific to each child. Future research should therefore delineate whether the effects of Improvisational Music

Improvisational Music Therapy for Children with ASD

Therapy may differ between verbal and nonverbal children, as well as across existing levels of joint attention and turn-taking skills, in order to understand how to better support children with ASD by individually tailoring music therapy programs.

References Aigen, K. (1995). Cognitive and affective processes in music

therapy with individuals with developmental delays: A

preliminary model for contemporary Nordoff-Robbins practice. Music Therapy, 13(1), 13-46.

Aigen, K. S. (2001). Popular musical styles in Nordoff-Robbins

clinical improvisation. Music Therapy Perspectives,

19(1), 31-44.

Baron-Cohen, S. (1987). Autism and symbolic play. British

Journal of Developmental Psychology, 5, 139-148.

Carpente, J. A. (2014). Individual music-centered assessment

profile for neurodevelopmental disorders (IMCAP-

ND): New developments in music-centered evaluation. Music Therapy Perspectives, 32(1), 56-60.

Crane, H. (2015). Music therapy and the treatment of children

diagnosed with Autism Spectrum Disorder. Lucerna,

10, 110-120.

Edgerton, C. L. (1994). The effect of Improvisational Music

Therapy on the communicative behaviors of Autistic children. Journal of Music Therapy, 31(1), 31-62.

Gold, C., Wigram, T., & Elefant, C. (2006). Music therapy

for Autistic Spectrum Disorder. The Cochrane

Database of Systematic Reviews, 2, 1-9.

Harril, K., & Jones, T. (2009). Structuring music therapy

sessions for individuals with Autism Spectrum

Disorders. In S. Brooke (Ed.), The use of creative

therapies with Autism Spectrum Disorders (pp. 199-

221). Springfield, IL: Charles C. Thomas.

Kanner, L. (1943). Autistic disturbances of affective contact.

Nervous Child, 2, 217-250.

Kim, J., Wigram, T., & Gold, C. (2008). The effects of

Improvisational Music Therapy on joint attention

behaviors in Autistic children: A randomized

controlled study. Journal of Autism and Developmental Disorders, 38(9), 1758-1766.

LaGasse, B. (2017). Social outcomes in children with Autism

Spectrum Disorder: A review of music therapy outcomes. Patient Related Outcome Measures, 8, 23- 32.

Lim, H. A. (2009). Use of music to improve speech production

in children with Autism Spectrum Disorders:

Theoretical orientation. Music Therapy Perspectives,

27(2), 103-114.

Nordoff, P., & Robbins, C. (1977). Creative music therapy. New

York, NY: John Day. Pasiali, V., LaGasse, A. B., & Penn, S. L. (2014). The effect of

musical attention control training (MACT) on

attention skills of adolescents with neurodevelopmental

delays: A pilot study. Journal of Music Therapy, 51(4), 333-354.

Staff Articles & Submissions | 9

Online Publication of Undergraduate Studies 2017, Volume 8, Issue 2 Simpson, K., & Keen, D. (2011). Music interventions for

children with Autism: Narrative review of the literature.

Journal of Autism and Developmental Disorders, 41, 1507-1514.

Spiro, N., & Himberg, T. (2016). Analysing change in music

therapy interactions of children with communication difficulties. Philosophical Transactions of the Royal

Society B: Biological Sciences, 371(1693), 1-11.

Vaiouli, P., Grimmet, K., & Ruich, L. J. (2015). “Bill is now

singing�: Joint engagement and the emergence of social

communication of three young children with autism.

Autism: The International Journal of Research and Practice, 19(1), 73-83.

Wigram, T., & Gold, C. (2006). Music therapy in the assessment

and treatment of Autistic Spectrum Disorder: Clinical

application and research evidence. Child Care, Health

& Development, 32(5), 535-542.

Wimpory, D., Chadwick, P., & Nash, S. (1995). Brief report:

Musical Interaction Therapy for children with Autism:

An evaluative case study with two-year follow-up.

Journal of Autism and Developmental Disorders,

25(5), 541-552.

10 | Staff Articles & Submissions

Improvisational Music Therapy for Children with ASD

Online Publication of Undergraduate Studies 2017, Volume 8, Issue 2

Agonist Therapies and Employability

Post-Treatment Employability Among Recovered Heroin Addicts: The Role of Agonist Therapies Samantha Valley

Over 2 million people in the United States are addicted to Opiates, of whom 467,000 are addicted to heroin (American Society of Addiction Medicine, 2011; NIH, 2014). Defined as a primary, chronic, and relapsing brain disease (ASAM, 2011), heroin addiction poses severe threats to an individual’s physical and mental health, and their ability to lead normal lives posttreatment (NIH, 2014; Whelan & Remski, 2012). In fact, the effects of heroin addiction are long-lasting, and persist both during and after an addict’s recovery – thereby presenting challenges to assimilation and employment (ASAM, 2011; Hunt, Lipton, Goldsmith, & strug, 1984; NIH, 2014). In light of these challenges, research has sought ways to support the posttreatment employability of heroin addicts (Hunt et al., 1984; NIH, 2014). In particular, findings suggest that agonist therapy medications may be effective in reducing the likelihood of later relapse (Hunt et. al., 1984; Whelan & Remski, 2012); how this effect translates into employability, however, is less clear. This paper thus aimed to explore the ways in which agonist therapies are associated with the employability of recovered heroin addicts.

Post-Treatment Employability of Heroin Addicts

As a highly addictive substance, heroin encourages a physical dependency that severely impairs one’s overeall functioning. Indeed, more than 23% of first-time heroin users eventually become addicted (ASAM, 2011; CDC, 2015; Goldstein, 1972), leading many to use the terms “recovered” and “recovery” interchangeably given the lifelong nature of the recovery process (i.e., the effects of substance abuse follow the recovered person throughout their lifetime; Koston & George, 2002; NIH, 2014). As such, the inability to effectively use judgment in decision making, as well as the lingering effects of psychological damage (e.g., anxiety, depression, the lack of impulse control; ASAM, 2011), and greater physical risk (e.g., Hepatitis B and C, HIV, falling into a coma; Koston & George, 2002; NIH, 2014), follows the addict long after recovery.

Consequently, employability – or the combination of experience, cognitive understanding, knowledge of trade, trade skills, interpersonal skills, self esteem, and emotional intelligence required to obtain work (Dacre Pool & Sewell, 2007; Law & Watts, 1997; Yorke & Knight, 2004) – is an issue of concern for various heroin addicts. In particular, addicts face barriers to employment within the domains of cognitive understanding, interpersonal skills, self esteem, and emotional intelligence, all of which represent aspects of effective communication (Callahan et al., 2016; Kemp & Neale, 2005; Law & Watts, 1997; Dacre Pool

& Swell, 2007; Yorke & Knight, 2004). The effects which impair one’s understanding of nonverbal cues, use of judgement, interpersonal skills, and emotional control make effectively communicating to an employer both prior to (e.g., the interview phase) and during work particularly challenging (Callahan et al., 2016; Giannini & Jones, 1985). These interpersonal skills, in turn, are further compounded by the post-treatment effects of poor sleeping and eating schedules, problems with authority, a criminal history due to inebriation, and mental health issues associated from drug withdrawal, making it especially difficult for recovered addicts to obtain and maintain employment (Callahan et al., 2016; Kemp & Neale, 2005).

Employability and the Role of Agonist Therapies

Research has since underscored the prescription of agonist therapies in order to mitigate these symptoms that linger post-treatment (Hunt et. al., 1984; Whelan & Remski, 2012).

Buprenorphine and Methadone represent two common agonist therapies prescribed to heroin addicts, both of which reduce withdrawal symptoms and feelings of craving by activating pleasure centers in the brain involved with opiate use (Tenore, 2008; Wakeman, 2016; Whelan & Remski, 2012). Furthermore, whereas those with mild to moderate heroin dependency tend to be prescribed Buprenorphine as a partial opioid, individuals with severe dependency are typically prescribed Methadone as a full opioid (Tenore, 2008; Whelan & Remski, 2012).

Specifically, Methadone acts as synthetic heroin in order to alleviate side effects of withdrawal and prevent relapse (Whelan & Remski, 2012), and is administered once a day in oral liquid form (Whelan & Remski, 2012). Several severe symptoms of Methadone exist, however, and include slurred speech, dependence, overdose, and an altered sense of reality (ASAM, 2011; NIH, 2014); these symptoms, in turn, serve as impediments to later employment (Hunt et. Al., 1984; Whelan & Remski, 2012), especially given the role communication skills play in obtaining and maintaining employment. By contrast, Buprenorphine is less potent, with withdrawal symptoms that are significantly less severe than those of Methadone (Whelan & Remski, 2012). In fact, Buprenorphine users have a reduced likelihood of overdosing and developing addictions given the ceiling effect of Buprenorphine (i.e., a maximum amount of stimulation is experienced irrespective of how much Buprenorphine is administered; Whelan & Remski, 2012), thereby leading some to advocate for the use of Buprenorphine as a function of reintegration into the vocational Staff Articles & Submissions | 11

Online Publication of Undergraduate Studies 2017, Volume 8, Issue 2 world (e.g., only 4.1% of those prescribed and administered Buprenorphine eventually relapse; Clark et al., 2014). However, and despite the reduced side effects on interpersonal abilities (ASAM, 2011; Hunt et al., 1984; NIH, 2014), because of its form, Buprenorphine is easier to inject than methadone, making the risk of injection higher than that of Methadone (Whelan & Remski, 2012). The misuse of Buprenorphine is also welldocumented, as many people illicitly abuse Buprenorphine as a pain killer rather than a means to achieve euphoria (Whelan & Remski, 2012). It is thus evident that Methadone creates a much broader impact on one’s communication abilities, whereas Buprenorphine is milder in its effects and poses less severe implications to one’s employability (ASAM, 2011; Hunt et al., 1984; NIH, 2014).

Conclusion

Current research on agonist therapies, heroin addiction, and post-treatment employability has shown that while Methadone and Buprenorphine are effective in relieving symptoms of opiate withdrawal, they may cause effects that inhibit the addict’s ability to become employed (Kemp & Neale, 2005). Communication skills are essential in job seeking, and if either of these agonist therapies significantly impair one’s ability to effectively communicate, they are hindering the addict’s ability to live a normal life after addiction (Hunt et al., 1984).

These findings, however, do not take into account the extent to which agonist therapies may increase or reduce an addict’s ability to assimilate into the real world after recovery (Callahan et al., 2016; Giannini & Jones, 1985). In light of the unique differences and challenges associated with each form of agonist therapy, as well as the various symptoms experienced by recovered heroin addicts, it is difficult to discern between which effects stem from long-term heroin abuse and the agonist therapies themselves (Callahan et al., 2016; Giannini & Jones, 1985). Investigating the various effects arising from Buprenorphine and Methadone as it relates to the recovering addict’s reintegration and employment would thus assist psychiatrists in determining where an addicts’ post-treatment symptoms stem from to better support their integration and employability.

Future research investigating the association between Buprenorphine or Methadone use and a person’s ability to assimilate into the real world also poses implications for policy.

Various governmentally-funded resources are currently being offered to recovered addicts. Some have advocated for recovered addicts to receive the same benefits as those with other cognitive, psychological, and physical disabilities, given the immense deficiencies in communication and interpersonal skills that make employment for the recovered addict particularly difficult (Giannini & Jones, 1985; Kemp & Neale, 2005). In fact, research shows that heroin addicts are the least likely to find employment after recovery as compared to other substance addicts (Callahan et al., 2016; Kemp & Neale, 2005). Understanding whether this outcome stems from heroin addiction itself, or the various treatments undertaken by recovered addicts, will uncover better 12 | Staff Articles & Submissions

Agonist Therapies and Employability

means to support their reintegration.

References American Society of Addiction Medicine. (2011). Public

Policy Statement: Definition of Addiction. Chevy

Chase, MD: American Society of Addiction Medicine.

Available at http://www.asam.org/docs/publicypolicy statements/1definition_of_addiction_long_4-11. pdf?sfvrsn=2 Ball, J. C., & Ross, A. (2012). The effectiveness of methadone

maintenance treatment: Patients, programs, services,

and outcome. New York, NY: Springer.

Callahan, S., LoSasso, A., Olson, B., Beasley, C., Nisle, S.,

Campagna, K., & Jason, L. A. (2015). Income generation

in recovering heroin users: A comparative analysis of

legal and illegal earnings. Journal of Offender Rehabilitation, 54(5), 338-349.

CDC. (2015). Today’s heroin epidemic. Center for Disease

Control and Prevention. Retrieved from https://www. cdc.gov/vitalsigns/heroin/index.html Dacre Pool, L., & Sewell, P. (2007). The key to employability:

Developing a practical model of graduate employability.

Education and Training, 49(4), 277-289.

Giannini, A. J., & Jones, B. T. (1985). Decreased reception of

nonverbal cues in heroin addicts. The Journal of Psychology, 119(5), 455-459.

Goldstein, A. (1972). Heroin addiction and the role of methadone

in its treatment. Archives of General Psychiatry, 26(4), 291-297.

Hunt, D. E., Lipton, D. S., Goldsmith, D., & Strug, D. (1984).

Street pharmacology: Uses of cocaine and heroin in the

treatment of addiction. Drug and Alcohol Dependence,

13(4), 375-387.

Kemp, P. A., & Neale, J. (2005). Employability and problem drug users. Critical Social Policy, 25(1), 28-46.

Kosten, T. R., & George, T. P. (2002). The neurobiology of opioid

dependence: Implications for treatment. Science &

Practice Perspectives, 1(1), 13-20.

National Institute of Health (2014). The role of opioids in

the treatment of chronic pain. Office of Disease Prevention. Retrieved from https://prevention.nih.gov/ programs-events/pathways-to-prevention/workshops/ opioids-chronic-pain Tenore, P. L. (2008). Psychotherapeutic benefits of opioid agonist therapy. Journal of Addictive Diseases, 27(3), 49-65.

Wakeman, S. E. (2016). Using science to battle stigma in

addressing the opioid epidemic: Opioid agonist therapy

saves lives. The American Journal of Medicine, 129(5), 455-456.

Whelan, P. J., & Remski, K. (2012). Buprenorphine vs.

methadone treatment: A review of evidence in both

developed and developing worlds. Journal of

Neurosciences in Rural Practice, 3(1), 45-50.

Online Publication of Undergraduate Studies 2017, Volume 8, Issue 2

Discrimination Against LGBT Community

Overt and Covert Discrimination Against the LGBT Community Peter Goldie

Approximately 3.8% of the United States population self-identify as members of the LGBT community, which consists of lesbian, gay, bisexual, and transgender individuals (Gates, 2011). The LGBT community-at-large is at an increased risk of a variety of mental health issues (Williams & Mann, 2017), including suicidal ideation (Blosnich, Bossarte, & Silenzio, 2012; Russell & Joyner, 2001), substance use disorders (Gilman et al., 2001; Lock & Steiner, 1999), and other anxiety and mood disorders (Gilman et al., 2001). Research suggests that these negative outcomes are often explained by experiences of discrimination, which are rooted in a lack of acceptance of the LGBT community among the general public (Herek, Gillis, & Cogan, 1999; Rodgers, 2017). For instance, more than half of lesbian, gay, and bisexual individuals report feeling stigmatized, and about 20% have experienced sexuality-related hate crimes (Herek, 2009). Furthermore, transgender individuals and people of color are disproportionately represented as victims of homicide (National Coalition of Anti-Violence Programs, 2017), thereby denoting the importance of intersectional and marginalized identities (e.g., class, race) that shape experiences of violence and oppression among the LGBT community (Crenshaw, 1991).

Furthermore, research suggests that discrimination manifests in both overt and covert forms, both of which are psychologically damaging (Tarquin & Cook-Cottone, 2008).

Whereas overt discrimination consists of verbal abuse and physical violence (Bhui et al., 2005), covert discrimination which includes microaggressions (Hatzenbuehler & Pachankis, 2016), whispers (McNeil et al., 2012), and social exclusion (Tarquin & Cook-Cottone, 2008) - manifests in more subtle and implicit ways (Bhui et al., 2005; McNeil, Bailey, Ellis, Morton, & Regan, 2012). Past research, however, has yet to differentiate the effects of LGBT oppression as a function of its overt and covert forms. In order to better equip practitioners in tailoring treatments or interventions that mitigate the negative effects of discrimination, this paper explores how overt and covert discrimination psychologically impacts LGBT-identifying individuals.

Overt Discrimination Against LGBT People

LGBT individuals face various psychologically destructive forms of overt discrimination (Hunter, 2007).

For instance, certain forms of physical violence against LGBT individuals (e.g., attempted assaults with weapons) have increased in recent years (Dworkin & Yi, 2003), thereby

increasing individuals’ risk for anxiety and depression (Bebanic, Clench-Aas, Raanaas, & Nes, 2015). The risk of experiencing rumination and feelings of loneliness is also heightened by exposure to violence, which creates an environment for LGBT people characterized by toxic levels of stress (Hatzenbuehler & Pachankis, 2016; Herek, 2009). Greater exposure to toxic stress, in turn, is particularly problematic as it leads to the release of unsafe levels of cortisol known to weaken the immune system and increase one’s susceptibility to infections (Lundberg, 2005). In fact, chronic stress is likely to detrimental for LGBT children, as it may disrupt the growth of key brain structures such as the HPA axis (Kaufman & Charney, 2001).

Experiences of overt discrimination in the home setting may also be a source of chronic stress, especially as LGBT individuals tend to lack strong family support systems (Martinez & McDonald, 2016). LGBT siblings are at a greater risk of being physically abused and kicked out of the home (Hunter, 2007), thereby contributing to disproportionately high rates of homelessness in LGBT youth (Corliss, Goodenow, Nichols, & Austin, 2011; Cray, Miller, & Durso, 2013). Once homeless, LGBT people fare poorly, attempting suicide more often than their non-LGBT counterparts (Van Leeuwen et al., 2006). As such, it is clear that overt forms of discrimination extend across various environments and pose significant implications for LGBT individuals.

Covert Discrimination Against LGBT People

While more subtle than overt discrimination, experiences of covert discrimination are equally problematic for LGBT people (Tarquin & Cook-Cottone, 2008). For example, lesbian, gay, and bisexual people commonly experience covert discrimination in the form of microaggressions, which are subtle and often unconscious actions which communicate hostility and devalue members of minority populations in a variety of different ways (Nadal, Whitman, Davis, Erazo, & Davidoff, 2016).

LGBT individuals commonly experience microaggressions in the form of statements that deny the presence of homophobia or transphobia in contemporary society, or that negate a gay person’s homosexuality, both of which invalidate the oppression faced by members of the LGBT community (Sue et al., 2007; Swann, Minshew, Newcomb, & Mustanski, 2016). Stress stemming from microaggressions toward LGBT people, in turn, is associated with mental health concerns such as depressive symptoms (Swann et al., 2016). Furthermore, microaggressions often increase LGBT individuals’ feelings of distress and disrupt Staff Articles & Submissions | 13

Online Publication of Undergraduate Studies 2017, Volume 8, Issue 2 the healthy development of a sexual identity (Hong, Woodford, Long, & Renn, 2016). It must also be noted that microaggressions affect specific subgroups of the LGBT community (e.g., bisexual people) and LGBT people of color in different ways (Balsam, Molina, Beadnell, Simoni, & Walters, 2011; Nadal et al., 2016).

For example, a transgender lesbian black woman will likely face a more severe set of microaggressions than a cisgender gay white man will.

Furthermore, social exclusion is another form of covert discrimination which has been suggested to have destructive effects on LGBT individuals’ mental health (Tarquin & CookCottone, 2008). In fact, it is common for others to avoid LGBT individuals, especially after they come out (Corrigan & Matthews, 2003). This often leaves LGBT people feeling alienated and lonely, diminishes their self-confidence (Corrigan & Matthews, 2003; Tarquin & Cook-Cottone, 2008), and can increase their risk of developing issues related to depression, anxiety and substance abuse (Lock & Steiner, 1999).

A similarly alienating form of covert discrimination is the lack of representation of LGBT characters in both American (Gomillion & Giuliano, 2011) and global (Santos, 2016) media.

Research suggests that gay, lesbian, and bisexual people are negatively affected by media invisibility and often feel excluded from society (Gomillion & Giuliano, 2011). Furthermore, such discrimination may lead to the internalization of heterosexism even among LGBT individuals; this internalization, in turn, has been demonstrated to be associated with depression, anxiety, substance abuse, stress, and personal devaluation (Herek, 1998; Lock & Steiner, 1999; Newcomb & Mustanski, 2010).

Furthermore, research demonstrates that there is a dearth of positive images of queer people of color in particular (Lopez, 2015); thus, for this group within the LGBT community, the negative effects of racism compound onto the heterosexism experienced more broadly among the LGBT community.

Nevertheless, while the lack of media representation for the community is damaging, it is promising that there have been an increasing number of, and diversity in, LGBT characters in recent years (Kelso, 2015).

Conclusion

In sum, research suggests that the various forms discrimination that LGBT people face are severely psychologically damaging (Almeida, Johnson, Corliss, Molnar, & Azrael, 2009). While overt and covert forms of discrimination manifest differently, the detrimental effects they produce share several similarities (e.g., increased risk for developing anxiety and depression). Understanding that these outcomes are common across overt and covert discrimination can inform the development of comprehensive interventions. For example, recognizing that both forms of discrimination often lead to depression and anxiety in LGBT individuals might prompt researchers to recommend responding to experiences of discrimination using cognitive-behavioral therapy, which has been suggested to mitigate such symptoms (García-Escalera, 14 | Staff Articles & Submissions

Discrimination Against LGBT Community

Chorot, Valiente, Reales, & Sandín, 2016). Future research should also identify protective factors for LGBT individuals who have experienced discrimination. For instance, interpersonal support might mitigate the problematic effects of heterosexism and discrimination (Hong et al., 2016), and represents a promising area for future intervention research. However, intervention and treatment for LGBT individuals must be supported by additional research on the the combined effects of heterosexism and racism, ableism, classism, and other forms of discrimination that affect LGBT individuals who are also part of other minority groups (Huang et al., 2010).

In addition to tailoring support to the experiences of discrimination among LGBT individuals, research must also identify means of decreasing heterosexism among society-atlarge. School-based interventions represent one key means of reducing discrimination, by promoting LGBT tolerance among future generations while their attitudes towards the LGBT community are still developing. Interventions aimed at shifting beliefs about LGBT individuals are the most effective means of supporting the LGBT community, as they would prevent discrimination before it occurs rather than simply managing its negative effects.

References Almeida, J., Johnson, R., Corliss, H., Molnar, B., & Azrael, D.

(2009). Emotional distress among

LGBT youth: The influence of perceived discrimination

based on sexual orientation. Journal of Youth and

Adolescence, 38(7), 1001-1014.

Aronson, E., & Aronson, J. (2012). The social animal. San

Francisco, CA: Freeman.

Balsam, K., Molina, Y., Beadnell, B., Simoni, J., & Walters, K.

(2011). Measuring multiple minority stress: The LGBT

People of Color Microaggressions scale. Cultural

Diversity and Ethnic Minority Psychology, 17(2), 163- 174.

Bebanic, V., Clench-Aas, J., Raanaas, R., & Nes, R. (2015). The

relationship between violence and psychological

distress among men and women: Do sense of mastery

and social support matter? Journal of Interpersonal

Violence, 32(16), 2371-2395.

Bhui, K., Stansfeld, S., McKenzie, K., Karlsen, S., Nazroo, J., &

Weich, S. (2005). Racial/ethnic discrimination and

common mental disorders among workers: Findings

from the EMPIRIC study of ethnic minority groups

in the united kingdom. American Journal of Public

Health, 95(3), 496-501.

Blosnich, J., Bossarte, R., & Silenzio, V. (2012). Suicidal ideation

among sexual minority veterans: Results from the

2005–2010 Massachusetts Behavioral Risk Factor

Surveillance Survey. American Journal of Public

Health, 102(S1), 44-47.

Online Publication of Undergraduate Studies 2017, Volume 8, Issue 2 Corliss, H., Goodenow, C., Nichols, L., & Austin, S. (2011). High

burden of homelessness among sexual-minority

adolescents: Findings from a representative

Massachusetts high school sample. American Journal

of Public Health, 101(9), 1683-1689.

Corrigan P., & Matthews A. (2003). Stigma and disclosure:

Implications for coming out of the closet. Journal of

Mental Health, 12(3), 235-248.

Cray, A., Miller, K., & Durso, L. (2013). Seeking shelter: The

experiences and unmet needs of LGBT homeless youth. Washington, DC: Center for American Progress.

Crenshaw, K. (1991). ‘Mapping the margins’: Intersectionality,

identity politics, and violence against women. Stanford

Law Review 43(6), 1241-1299.

Dworkin, S., & Yi, H. (2003). LGBT identity, violence, and social

justice: The psychological is political. International

Journal for the Advancement of Counselling, 25(4), 269-279.

García-Escalera, J., Chorot, P., Valiente, R., Reales, J., & Sandín,

B. (2016). Efficacy of transdiagnostic Cognitive Behavioral Therapy for anxiety and depression in

adults, children and adolescents: A meta-analysis.

Revista de Psicopatología y Psicología Clínica, 21(3), 147-175.

Gates, G. (2010). How many people are lesbian, gay,

bisexual, and transgender? Retrieved from https:// williamsinstitute.law.ucla.edu/wp-content/uploads/ Gates-How-Many-People-LGBT-Apr-2011.pdf Gilman, S., Cochran, S., Mays, V., Hughes, M., Ostrow, D.,

& Kessler, R. (2001). Risk of psychiatric disorders

among individuals reporting same-sex sexual partners

in the National Comorbidity Survey. American

Journal of Public Health, 91(6), 933-939.

Gomillion, S. & Giuliano, T. (2011). The influence of media

role models on gay, lesbian, and bisexual identity.

Journal of Homosexuality, 58(3), 330-354.

Hatzenbuehler, M., & Pachankis, J. (2016). Stigma and minority

stress as social determinants of health among lesbian,

gay, bisexual, and transgender youth. Pediatric Clinics

of North America, 63(6), 985-997.

Herek, G. (1998). Stigma and sexual orientation: Understanding

prejudice against lesbians, gay men, and bisexuals.

Newbury Park, CA: Sage.

Herek, G. (2009). Hate crimes and stigma-related experiences

among sexual minority adults in the United States.

Journal of Interpersonal Violence, 24(1), 54-74.

Herek, G., Gillis, J., & Cogan, J. (1999). Psychological sequelae

of hate-crime victimization among lesbian, gay, and

bisexual adults. Journal of Consulting and Clinical

Psychology, 67(6), 945-951.

Hong, J., Woodford, M., Long, L., & Renn, K. (2016). Ecological

covariates of subtle and blatant heterosexism

discrimination among LGBQ college students. Journal

of Youth and Adolescence, 45(1), 117-131.

Discrimination Against LGBT Community

Huang, Y., Brewster, M., Moradi, Goodman, M., Wiseman, M.,

& Martin, A. (2010). Content analysis of literature

about lesbian, gay, and bisexual people of color: 1998- 2007. The Counseling Psychologist, 38(3), 363-396.

Hunter, S. (2007). Coming out and disclosures: LGBT persons

across the life span. New York, NY: Haworth Press.

Kaufman, J., & Charney, D. (2001). Effects of early stress on

brain structure and function: Implications for

understanding the relationship between child

maltreatment and depression. Developmental

Psychopathology, 13(3), 451-71.

Kelso, T. (2015). Still trapped in the U.S. media’s closet:

Representations of gender-variant, pre-adolescent children. Journal of Homosexuality, 62(8), 1058-1097.

Lock J., & Steiner, H. (1999). Gay, lesbian, and bisexual youth

risks for emotional, physical, and social

problems: Results from a community-based survey.

Journal of the American Academy of Child and

Adolescent Psychiatry 38(3), 297-304.

Lopez, L. (2015). A media campaign for ourselves: Building

organizational media capacity through participatory

action research. Journal of Media Practice, 16(3), 228- 244.

Lundberg, U. (2005). Stress hormones in health and illness: The

roles of work and gender. Psychoneuroendocrinology, 30(10), 1017-1021.

Martinez, K., & McDonald, C. (2016). By the hands of our

brothers: An exploration of sibling-to-sibling

aggression for victimized heterosexual and sexual

minority women. Journal of GLBT Family Studies, 12(3), 242-256.

McNeil, J., Bailey, L., Ellis, S., Morton, J., & Regan, M. (2012).

Trans mental health study 2012. Scottish Transgender Alliance. Retrieved from http://www.scottishtrans.org/ Uploads/Resources/trans_mh_study.pdf Nadal, K., Whitman, C., Davis, L., Erazo, T., & Davidoff,

K. (2016). Microaggressions toward lesbian, gay,

bisexual, transgender, queer, and genderqueer people:

A review of the literature. The Journal of Sex Research, 53(4-5), 488-508.

National Coalition of Anti-Violence Programs. (2017). Lesbian,

gay, bisexual, transgender, queer, and HIV-affected

hate violence in 2016. Retrieved from https://avp.org/ wp-content/uploads/2017/06/ NCAVP_2016HateViolence_REPORT.pdf National Childhood Traumatic Stress Network. (n.d.). Effects

of complex trauma. Retrieved from http://www.

nctsn.org/trauma-types/complex-trauma/effects-of- complex-trauma Newcomb, M., & Mustanski, B. (2010). Internalized homophobia

and internalizing mental health problems: A meta analytic review. Clinical Psychology Review, 30(8), 1019-1029.

Staff Articles & Submissions | 15

Online Publication of Undergraduate Studies 2017, Volume 8, Issue 2 Rodgers, S. (2017). Transitional age lesbian, gay, transgender,

and questioning youth. Child and Adolescent

Psychiatric Clinics of North America, 26(2), 297-309.

Russell, S., & Joyner, K. (2001). Adolescent sexual orientation

and suicide risk: Evidence from a national study.

American Journal of Public Health, 91(8), 1276-1281.

Santos, A. (2016). ‘In the old days, there were no gays’ -

Democracy, social change and media representation

of sexual diversity. International Journal of Iberian

Studies, 29(2), 157-172.

Sue, D. (2010). Microaggressions in everyday life: Race, gender,

and sexual orientation. Hoboken, NJ: John Wiley & Sons.

Sue, D., Capodilupo, C., Torino, G., Bucceri, J., Holder, A., Nadal,

K., & Esquilin, M. (2007). Racial microaggressions

in everyday life: Implications for counseling. American

Psychologist, 62(4), 281-286.

Swann, G., Minshew, R., Newcomb, M., & Mustanski, B. (2016).

Validation of the sexual orientation microaggression

inventory in two diverse samples of LGBTQ youth.

Archives of Sexual Behavior, 45(6), 1289-1298.

Tarquin, K., & Cook-Cottone, C. (2008). Relationships among

aspects of student alienation and self concept. School

Psychology Quarterly, 23(1), 16-25.

Van Leeuwen, J., Boyle, S., Salomonsen-Sautel, S., Baker, D.,

Garcia, J., Hoffman, A., & Hopfer, C. (2006). Lesbian,

gay, and bisexual homeless youth: An eight-city public

health perspective. Child Welfare, 85(2), 151-170.

Williams, S., & Mann, A. (2017). Sexual and gender minority

health disparities as a social issue: How stigma and

intergroup relations can explain and reduce health disparities. Journal of Social Issues, 73(3), 450-461.

16 | Staff Articles & Submissions

Discrimination Against LGBT Community

Online Publication of Undergraduate Studies 2017, Volume 8, Issue 2

Female Youth’s Dress

Female Youth’s Dress in the Courtroom: Implications for Judicial Sentencing Severity Christina Ducat

In 2015, females accounted for 38% of juveniles placed in detention for status offenses (e.g., low-level, nonviolent crimes such as running away, truancy, curfew violations, underage drinking, and incorrigibility; Sickmund, Sladky, Kang, & Puzzanchera, 2017), despite representing only 15% of residential placements (Office of Juvenile Justice & Delinquency Prevention, 2015). In fact, girls are arrested, petitioned to court, and placed in detention facilities for less severe offenses at a disproportionate rate compared to boys: whereas status offenses represent 12% of girls’ residential placement, similar offenses account for only 4% of boys’ offenses (Sickmund et al., 2017).

This trend in asymmetrical sentencing speaks to the double standard that exists for boys and girls involved in the juvenile justice system (Chesney-Lind & Pasko, 2013).

Gender differences alone, however, do not account for all the variation in the sentencing severity of female defendants; defendants who are tried on the exact same charges receive sentences of varying severity depending on judges’ perceptions of any given defendant (Doerner & Demuth, 2010). In particular, research suggests that physical appearance in the courtroom may be an individual-level characteristic that systematically impacts sentencing severity (Fontaine & Kiger, 1978). As girls who dress in accordance with stereotypical feminine norms tend to be given shorter and less severe sentences than those who deviate from them (Chesney-Lind & Pasko 2013), it is plausible that the way a girl chooses to dress in court might affect how a judge perceives her and in turn the severity of her sentence (Davis, 1992, Fontaine & Kiger, 1978). Drawing upon defensive attribution theory, it is evident that judges’ perceptions are subject to influence by extralegal factors that impact their sentencing (Danziger, Levav, & Avnaim-Pesso, 2010; Shaver, 1970). However, despite the recent increase in the number of young women tried in juvenile delinquency cases and the notable increase in female incarceration rates (Carson, 2015; Hockenberry & Puzzanchera, 2015), there remains a paucity of research focusing on how judges’ and juries’ perceptions of female defendants are associated with differences in courtroom experience. As such, this paper aims to address the aforementioned gap in the literature by exploring the relation between the physical expression of gender (e.g., dress) and judges’ perceptions of the defendant, and how these perceptions relate to sentencing severity.

Clothing Choice and The Female Court Experience

While an ideal judge is objective and sentences strictly according to the facts of a case (Guthrie, Wistrich, & Rachlinski, 2007), external or extralegal factors such as physical appearance and dress influence how the judge perceives the defendant’s guilt, and subsequently the severity of a judge’s sentence (Danziger et al., 2010; Doerner & Demuth, 2010; Fontaine & Kiger, 1978). The physical expression of individual characteristics is particularly salient as it is one of the first things a judge perceives about a defendant when hearing a case. In fact, the interpretation of these physical characteristics, including dress, is often informed by stereotypes (Gurney, Howlett, Pine, Tracey, & Moggridge, 2017). At the commencement of the case, judges may use the defendant’s physical appearance as a mechanism by which to derive meaning regarding who the defendant is, what they value (Davis, 1992), their confidence, professionalism, and overall approachability (Gurney et al., 2017), and their social status (Ridgeway, 1991). Furthermore, clothing choice is perceived as an expression of the defendant’s respect for the judge, and how seriously the defendant is treating the legal process – both of which inform the judge’s sympathy for the defendant (Petrucci, 2002). Such attributions, however, are not uniformly imposed across defendants (Doerner & Demuth, 2010; Fontaine & Kiger, 1978; Rokeach & Vidmar, 1973).

In particular, gender differences contribute to variations in courtroom experience (Javdani, Sadeh, & Verona, 2011), that arise from gender-specific norms of behavior (Chesney-Lind & Pasko, 2013). Girls are expected to adhere to gender norms and are punished for the failure to conform to such norms (Javdani et al., 2011). As compared to males, females are disproportionately subject to marginalization when they deviate from feminine norms. In particular, female behaviors that deviate from socially dictated gender norms are perceived as lapses in morality (Chesney-Lind & Eliason, 2006), which leads to the perception of girls as delinquent (Javdani et al., 2011). Such expectations surrounding conformity manifest within clothing choice, which are used to convey larger messages about who a person is and what they value (Davis, 1992). In the United States, norms of appropriate female dress are culturally operationalized as conservative yet feminine (Grubb & Turner, 2012); deviation from this ideal, in turn, is often met with punishment in the form of hostile sexism (Glick & Fiske, 1996).

As such, there exists a double standard: girls are expected to be obedient and embody traditional family values, whereas boys’ deviant behaviors are permissible in the courtroom because Staff Articles & Submissions | 17

Online Publication of Undergraduate Studies 2017, Volume 8, Issue 2 ‘boys will be boys’ (Chesney-Lind, 1977). If girls fail to comply with these courtroom standards, they are deemed aggressive or violent, and are more likely to be judged harshly and sentenced more severely as a result of their deviation from stereotypical norms of femininity (Chesney-Lind & Pasko, 2013; Petrucci, 2002). In the courtroom, this kind of punishment materializes through greater sentencing severity – explaining, at least in part, the imbalance in female incarceration rates (Carson, 2015; Chesney-Lind & Eliason, 2006; Javdani et al., 2011).

Judicial Perceptions and Sentencing Severity

There still, however, remains significant variability in the sentencing severity among female juveniles. Regardless of a defendant’s conformity to or deviation from gender norms, they are still subject to judges’ biases involving their individuallevel characteristics (e.g., gender and age; Doerner & Demuth, 2010). Value judgments are placed upon girls on the basis of physical appearance, and the resulting perceptions arising from value judgments have salient implications for the sentencing of a defendant (Cramer et al., 2013; Grubb & Turner 2012). The ways in which individuals – and specifically judges – assess physical appearance and make subsequent sentencing decisions is characterized by defensive attribution theory (Mitchell & Byrne, 1973; Shaver, 1970).

Defensive attribution theory explains a cognitive bias in which one is more likely to attribute fault to another individual if he or she perceives the other as being different from the self (Shaver, 1970). People use “common sense knowledge of social structures” to infer the motivations and relative social position of others (Garfinkel, 1967, p. 76), and one indicator of these social structures is physical appearance, including clothing choice (Davis, 1992; Forsythe, 1990). When the judge believes they share common ground or similar values with a defendant, they are more likely to rule in the defendant’s favor by affording them lenient sentences (Fontaine & Kiger, 1978; Shaver, 1970).

Conversely, it follows that where there is a perceived difference between the judge and the defendant, harsher sentences are more likely. As such, female defendants who deviate from stereotypical norms of dress may establish greater perceived differences between the defendant and the judge, given that the defendant conveys a different set of values than what the judge may hold (Grubb & Turner, 2012). This values-mismatch contributes to the variability in assigned culpability among individuals of similar personal characteristics and infractions (Cramer et al., 2013; Shaver, 1970), in which differences in perceived guilt or responsibility of a defendant result in variations in sentence severity for the same charges. In fact, women as a group are sentenced less severely than men for the same crimes; women who deviate from stereotypical feminine norms, however, are sentenced more severely than men who are charged with the same crimes (Chesney-Lind & Eliason, 2006; Chesney-Lind & Pasko, 2013). These findings suggest that greater expectations are placed on women in terms of adherence to gender norms, in that perceived deviation from these norms leads to more 18 | Staff Articles & Submissions

Female Youth’s Dress

severe punishment in the form of severe sentencing (Glick & Fiske, 1996; Grubb & Turner, 2012). It is thus evident that clothing represents one facet by which judges infer a defendant’s characteristics and guilt (Forsythe, 1990), that contributes to systematic differences in sentencing severity even among girls.

Discussion

Despite the empirical evidence that highlights the disadvantaged position of girls in the courtroom (Javdani et al., 2011), research involving the role of judicial bias in sentencing, and especially as it involves marginalized populations such as women and youth, is limited. In fact, only some research has investigated the role of variability in clothing type (e.g., defendants who wear institutional dress, such as prison jumpsuits) in being found guilty by a jury or receiving more severe sentences from a judge (Fontaine & Kiger, 1978).

Furthermore, the extant research surrounding the role of clothing choice in sentencing outcomes is largely based upon studies completed in the 1970’s and 80’s, with little continuing research. Addressing this gap is critical in light of changing societal norms surrounding dress, as well as the notable increase in female juvenile incarceration in recent years (Carson, 2015; Hockenberry & Puzzanchera, 2015). Future research should therefore closely investigate the ways social constructions of gender norms impact girls involved in the juvenile justice system, and how those norms might impact sentencing severity when judges are exposed to female defendants who differ in physical appearance but have nonetheless been charged with the same crime. Analyzing the consistency of judicial decisionmaking represents one significant step in moving towards an unbiased justice system, and a fuller understanding of the needs of this population. With this greater understanding, it becomes possible to effectively advocate for and work with girls in the justice system in a gender-responsive manner.

References Carson, E.A. (2015). Prisoners in 2014. U.S. Department of

Justice: Office of Justice Programs. Washington, D.C.:

Bureau of Justice Statistics.

Chesney-Lind, M. (1977). Judicial paternalism and the female

status offender: Training women to know their place.

Crime & Delinquency, 23(2), 121-130.

Chesney-Lind, M., & Eliason, M. (2006). From invisible to

incorrigible: The demonization of marginalized women

and girls. Crime Media Culture, 2(1), 29-47.

Chesney-Lind, M., & Pasko, L. (Eds.). (2013). Sentencing women

to prison: Equality without justice. In The female

offender: Girls, women, and crime (pp. 119 - 152).

Thousand Oaks, CA: Sage Publications.

Cramer, R., Gorter, E., Cornish Rodriguez, M., Clark, J., Rice,

A., & Nobles, M. (2013). Blame attribution in court:

Conceptualization and measurement of perpetrator blame. Victims & Offenders, 8(1), 42-55.

Online Publication of Undergraduate Studies 2017, Volume 8, Issue 2 Danziger, S., Levav, J., & Avnaim-Pesso, L. (2010). Extraneous

factors in judicial decisions. Proceedings of the

National Academy of Sciences of the United States of

America, 108(17), 6989-6892.

Davis, F. (1992). Do clothes speak? What makes them fashion?

In Fashion, Culture, and Identity (pp. 3-18). Chicago,

IL: University of Chicago Press.

Doerner, J., & Demuth, S. (2010). The independent and joint

effects of race/ethnicity, gender, and age on sentencing

outcomes in U.S. Federal Courts. Justice Quarterly, 27(1), 1-24.

Fontaine, G., & Kiger, R. (1978). The effects of defendant

dress and supervision on judgments of simulated

jurors: An exploratory study. Law and Human Behavior, 2(1), 63-71.

Forsythe, S. (1990). The effect of applicant’s clothing on

interviewer’s decision to hire. Journal of Applied Social

Psychology, 20(19), 1579-1595.

Garfinkel, H. (1984). Common sense knowledge of social

structures: The documentary method of

interpretation in lay and professional fact finding. In

Studies in Ethnomethodology (pp. 76-103). Cambridge,

United Kingdom: Polity Press.

Glick, P. & Fiske, S. (1996). The ambivalent sexism inventory:

Differentiating hostile and benevolent sexism. Journal

of Personality and Social Psychology, 70(3), 491-512.

Gurney, D., Howlett, N., Pine, K., Tracey, M., & Moggridge, R.

(2017). Dressing up posture: The interactive effects of

posture and clothing on competency judgments.

British Journal of Psychology, 108(2), 436-451.

Guthrie, C., Wistrich, A., & Rachlinski, J. (2007). Blinking on

the bench: How judges decide cases.

Scholarship@Cornell Law: A Digital Repository, 93(1), 1-44.

Grubb, A., & Turner, E. (2012). Attribution of blame in rape

cases: A review of the impact of rape myth acceptance,

gender role conformity and substance use on victim blaming. Aggression and Violent Behavior, 17(5), 443 452.

Hockenberry, S., & Puzzanchera C. (2015). Juvenile court

statistics 2013 report. National Center for Juvenile Justice. Retrieved from https://www.ojjdp.gov/ojstatbb/ njcda/pdf/jcs2013 Javdani, S., Sadeh, N., & Verona, E. (2011). Expanding our lens:

Female pathways to antisocial behavior in adolescence

and adulthood. Clinical Psychology Review, 31(8), 1324-1348.

Mitchell, H., & Byrne, D. (1973). The defendant’s dilemma:

Effects of juror’s attitudes and authoritarianism on

judicial decisions. Journal of Personality and Social

Psychology, 25(1), 123-129.

Female Youth’s Dress

Office of Juvenile Justice and Delinquency Prevention (2015).

Spotlight on Girls in the Juvenile Justice System.

Retrieved from: https://www.ojjdp.gov/ojstatbb/ snapshots/DataSnapshot_Girls2015.pdf Petrucci, C. (2002). Respect as a component in the judge defendant interaction in a specialized domestic

violence court that utilizes therapeutic jurisprudence.

Criminal Law Bulletin, 38(2), 263-297.

Ridgeway, C. (1991). The social construction of status value:

Gender and other nominal characteristics. Social

Forces, 70(2), 367-386.

Rokeach, M. & Vidmar, N. (1973). Testimony concerning

possible jury bias in a Black Panther murder trial.

Journal of Applied Social Psychology, 3(1), 19-29.

Shaver, K. (1970). Defensive attribution: Effects of severity and

relevance on the responsibility assigned for an accident.

Journal of Personality and Social Psychology, 14(2), 101-113.

Sickmund, M., Sladky, T., Kang, W., & Puzzanchera, C. (2017).

Census of juveniles in residential placement. Retrieved

from: http://www.ojjdp.gov/ojstatbb/ezacjrp/

Staff Articles & Submissions | 19

Online Publication of Undergraduate Studies 2017, Volume 8, Issue 2

Teachers’ Responses to Disruptive Behavior

Teachers’ Responses to Disruptive Behavior in Ethnically Diverse Early-Childhood Classrooms Elysha Clark-Whitney and Julius A. Utama

Throughout early childhood, children develop a variety of adaptive behaviors conducive to classroom learning (Hamre & Pianta, 2001; Jordan, Kaplan, Ramineni, & Locuniak, 2009).

Specifically, the ability to regulate emotions, inhibit inappropriate responses, and focus attention toward a given task (Blair & Razza, 2007; Raver, 2012), allows children to engage in classroom activities in accordance with their teachers’ expectations (Razza, Martin, & Brooks-Gunn, 2012; Williford, Maier, Downer, Pianta, & Howes, 2013). As such, researchers and policymakers have sought ways to support the development of adaptive behaviors during the preschool years as conduits for later academic success (Wanless, McClelland, Tominey, & Acock, 2011).

Research has identified, however, that disruptive behaviors common in the early years (e.g., hyperactivity, inattention, aggression) impede children’s ability to display adaptive classroom behaviors (Rimm-Kaufman, Pianta, & Cox, 2000; Wakschlag et al., 2007). The negative impact of disruptive behaviors is particularly detrimental for children from ethnically diverse, low-income backgrounds, who tend to exhibit more disruptive behaviors as compared to their White peers (Bradshaw, Mitchell, O’Brennan, & Leaf, 2010; Harris & Herrington, 2006), and are in turn at greater risk for academic difficulties and school dropout (Vitaro, Brendgen, Larose, & Tremblay, 2005).

Fostering adaptive behaviors in the early childhood years may therefore serve as a protective factor for the school success of children from ethnically-diverse, low-income backgrounds (Duncan et al., 2007; Galindo & Fuller, 2010; Wanless et al., 2011).

In particular, research has identified the importance of teachers’ behavior management practices (Howes et al., 2008; Degol & Bachman, 2015; Mashburn et al., 2008) – or the provision of feedback and monitoring of classroom activities (Hoy & Weinstein, 2006; Kunter, Baumert, & Koller, 2007; Yates & Yates, 1990) – in encouraging children’s development of adaptive behaviors (Raver, 2010). Specifically, teachers’ behavior management practices encourage children to be more cognizant of their own behaviors vis-à-vis classroom rules (Degol & Bachman, 2015; Rimm-Kaufman, Curby, Grimm, Nathanson, & Brock, 2009); the successful implementation of these management strategies, in turn, is associated with children’s school success (Pianta & Stuhlman, 2004; Qi & Kaiser, 2003), and especially the academic performance of ethnically diverse children (Curby, Downer, & Booren, 2014; Merritt, Wanless, Rimm- Kaufman, Cameron, & Peugh, 2012).

Despite this, however, little is known regarding the behavior management practices used by teachers in ethnically diverse 20 | Staff Articles & Submissions

classrooms. This is alarming given that schools across the United States are becoming increasingly multiethnic; in 2014 alone, over 50% of students in U.S. public schools identified as nonWhite (National Center for Education Statistics, 2013). In order to elucidate avenues to better support this at-risk population, the present study explored the behavior management practices teachers use in response to disruptive behaviors in ethnically diverse, low-income early childhood classrooms.

Disruptive Behaviors in Early Childhood: A Developmental Perspective

Across cultural groups, young children commonly engage in a wide variety of disruptive classroom behaviors (Rimm-Kaufman et al., 2000) such as defiance (i.e., actively refusing to follow a given instruction; Wakschlag et al., 2007), inattention (i.e., distractibility and difficulty attending to stimuli for long periods of time; Coolahan, Fantuzzo, Mendez, & McDermott, 2000; Racz, O’Brennan, Bradshaw, & Leaf, 2016), aggression (e.g., hitting and kicking; Wakschlag et al., 2007), hyperactivity (i.e., failing to remain still when expected to do so; Vitaro et al., 2005), and tantrums (Wakschlag et al., 2012).

These disruptive behaviors tend to interfere with children’s ontask behavior and classroom learning (Blair & Razza, 2007; McClelland et al., 2007; Rimm-Kaufman et al., 2009). While normative among young children, disruptive behaviors tend to decrease over the preschool years as a function of children’s growing self-regulation skills (Bulotsky-Shearer, Fantuzzo, & McDermott, 2008; Degnan, Calkins, Keane, & Hill-Soderlund, 2008; Garon, Bryson, & Smith, 2008), which are integral to children’s ability to inhibit inappropriate behaviors (Willoughby, Kupersmidt, Voegler-Lee, & Bryant, 2011). Wide variations in disruptive behaviors, therefore, are also common between children, given individual differences in development.

In particular, ethnic minority children are more likely than their White counterparts to exhibit frequent and intense disruptive behaviors (Kremer, Flower, Huang, & Vaughan, 2016). This can primarily be attributed to the destructive effect of chronic poverty, which is more common among ethnic minorities (U.S. Census Bureau, 2016), on self-regulation development (Blair, 2010). These more extreme disruptive behaviors interfere substantially with early learning, placing ethnic minority children at risk of later academic difficulty and school suspension (Qi & Kaiser, 2003; Racz et al., 2016). As such, research must identify effective ways to mitigate the disruptive behaviors of low-income, ethnic minority children.

Online Publication of Undergraduate Studies 2017, Volume 8, Issue 2 Teachers’ Behavior Management Strategies in Early Childhood Classrooms

Teachers’ behavior management practices represent one such mechanism for reducing children’s disruptive behaviors (Snyder et al., 2011; Webster-Stratton, Reid, & Stoolmiller, 2008). As proximal influencers of children’s regulated behaviors (Degol & Bachman, 2015; Rimm Kaufman et al., 2009; Wallace, Sung, & Williams, 2014), teachers socialize children through a “hidden behavioral curriculum” (i.e., in addition to an explicit academic curriculum; Martinez-Pons, 2002, p. 130) that is especially effective when implemented through a combination of positive and proactive behavior management strategies (Sugai & Horner, 2002). When teachers use positive disciplinary practices by reprimanding children’s actions (i.e., as opposed to targeting the child as an individual; Fuhs, Farran, & Nesbitt, 2013), children are more intrinsically motivated to master the task at hand (Clunies-Ross, Little, & Kienhuis, 2008); this increased motivation, in turn, leads children to remain on-task during subsequent iterations of the classroom activity (LeFlot, van Lier, Onghena, & Colpin, 2010). Additionally, teachers’ use of positive feedback, which consists of non-critical and non-restrictive statements (e.g., “I love how everyone is using their inside voices right now”), reduces children’s disruptive behaviors toward their teachers and peers (Mashburn & Pianta, 2006; Snyder et al., 2011).

In addition to positive behavior management, teachers’ proactive management practices – consisting of the provision and repetition of clear classroom rules and instructions (Kame’enui & Darch, 1995) – are also crucial for the reduction of children’s disruptive classroom behaviors (Jack et al., 1996; Mashburn et al., 2008; Raver et al., 2008; Sugai & Horner, 2002). When teachers reiterate classroom rules and the logical progression of classroom tasks (i.e., complete task A in order to complete task B; Snyder et al., 2011; Wallace et al., 2014), in addition to explicitly stating, giving examples of, and explaining the significance of children’s classroom behaviors, children are better able to associate their own behaviors with what is expected of them (Carter & Doyle, 2005; Delpit, 2006; Manke, 1997). Similarly, when teachers explicitly replace maladaptive behaviors with adaptive ones (e.g., verbalizing “walk inside the classroom,” as opposed to “no running in the classroom”), associate the role of adaptive behaviors as it relates to what is expected of a child within a given activity setting (Kounin, 1970), and proactively teach logical (e.g., “first finish your juice, then get in line”) and social-emotional (e.g., “inside voices make me really happy”) consequences to child behavior, children are more likely to retain adaptive (Williford & Shelton, 2014) and minimize disruptive (Degol & Bachman, 2015) behaviors in the future.

Teachers’ Responses to Disruptive Behavior

Behavior Management in Ethnically Diverse Classrooms

Studies involving best practices in behavior management, however, have largely been conducted with European American children (Gay, 2006). In particular, researchers have highlighted the culture-bound nature of behavior management practices and expectations for regulated behavior (Dearing, 2004; van Tartwijk & Hammerness, 2011), thereby complicating theories involving best practices of behavior management. Research consistently demonstrates that teachers vary in the ways they employ behavior management practices depending on their own culture’s controlling beliefs, emphasis on emotions and reflective processes (Ballenger, 1999; Weinstein, Tomlinson-Clarke, & Curran, 2004), and childcentered orientations (e.g., autonomy support; Koh & Shin, 2014; van Tartwijk & Hammerness, 2011). European American children, for example, are more accustomed to undertaking the role of the active participant in class discussions (Gay, 2006), whereas Latino children may be less likely to ask questions as a result of their own cultural socialization practices (Scarcella, 1990). African American children, on the other hand, are more likely to call out during classroom group interactions as a function of the call-and-response styles most commonly found in the home (Weinstein et al., 2004). As such, there is reason to suspect that children from ethnically diverse backgrounds may be exposed to management practices that differ between the home and school (Caughy & Owen, 2015; Li-Grining, 2012).

Furthermore, recent research on culturally responsive classroom management suggests that the ways in which teachers’ management practices are implemented (as opposed to the management practices themselves) are particularly predictive of children’s behavioral outcomes (Weinstein et al., 2004). In other words, it is the way in which behavior management practices are implemented (i.e., management modifiers; e.g., tone) that distinguishes culture-specific behavior management practices from one another (Wubbels, 2011). Yet, little is known regarding how teachers’ use of management modifiers differs in ethnically diverse classrooms.

Current Study

Few studies to date have explored if and how teachers navigate between recommended practices involving ethnic majority children and culture-specific methods of behavior management (Villegas & Lucas, 2002), and how these management strategies differ across child age and types of disruptive behavior. This is problematic given the increasing number of ethnically diverse classrooms in the United States (National Center for Education Statistics, 2013), and findings that children from low-income ethnic minority backgrounds are at greater risk of behavioral problems (Eisenberg et al., 2001; Howse, Lange, Farran, & Boyles, 2003; Razza, Martins, & Brooks-Gunn, 2010) and subsequent difficulties in school (Zimmerman, 1998). Thus, exploring teachers’ responses to disruptive behaviors represents a first step in identifying ways to support the school success of this at-risk population. As Staff Articles & Submissions | 21

Online Publication of Undergraduate Studies 2017, Volume 8, Issue 2 such, the present study poses the following research questions: (1) What are the disruptive behaviors most often exhibited by children in low-income, ethnically diverse early childhood classrooms? (2) What are the behavior management practices most often implemented by teachers in low-income, ethnically diverse early-childhood classrooms? (3) How do teachers’ behavior management practices differ depending on type of disruptive behavior? (4) How do teachers’ behavior management practices vary by child age?

Method Setting and Participants

Participants included teachers and children in two early childhood classrooms situated in low-income Spanish-speaking communities in New York City. Both classrooms were ethnically diverse (i.e., at least 85% of children were non-White).

Preschool classroom. The preschool observation was conducted in a Head Start classroom consisting of 16 three-yearold children, a lead teacher and an assistant teacher. The lead teacher was a female of African-American descent with over 20 years of teaching experience, whereas the assistant teacher was a Latina woman with four years of teaching experience.

Kindergarten classroom.

The kindergarten observation was conducted in a public kindergarten classroom consisting of 24 five-year-old children and one female lead teacher. The kindergarten teacher was of African-American descent with seven years’ teaching experience.

Procedure Sixteen field notes were collected over six months during weekly three-hour classroom volunteering periods. Observed activities in the preschool classroom consisted of drop-off, morning meeting, center time/free play, outdoor play, nap time, and meal time. On the other hand, observed activities in the kindergarten classroom consisted of drop-off, morning meeting, journal writing activities, library time, science time, and meal-time. To minimize participant reactivity, field notes were written immediately after classroom observations, taking particular note of the behavior management interactions that occurred throughout the observational period.

Researcher Stance

Both authors were participant observers and assisted in classroom activities in accordance with teachers’ needs (e.g., book reading, supervising outdoor play). In addition, both authors completed primary and secondary education outside the United States, and were raised in cultures distinct from the children and teachers observed.

Coding and Analysis

Field notes were coded using classical content analysis (Leech & Onwuegbuzie, 2008). Observations were first chunked by interaction; each chunk was then assigned one or more codes for child disruptive behavior and teacher behavior management 22 | Staff Articles & Submissions

Teachers’ Responses to Disruptive Behavior

(see Appendix). Codes were developed both inductively and deductively. The authors initially coded 50% of the data to obtain a reliability estimate (κ = .71); the remaining field notes were coded independently and verified together. To answer the first two research questions, frequencies of each code were calculated to estimate the prevalence of different types of disruptive behavior and behavior management practices in each classroom. In order to answer the third research question, frequencies of teachers’ behavior management practices (and their management modifiers) were calculated separately for each type of disruptive behavior, to discern patterns between types of disruptive behavior and behavior management practices.

To answer the fourth research question, overall findings were compared across the two classrooms.

Results and Discussion Frequency of Children’s Disruptive Behaviors

With regards to the first research question, of the 319 codes for disruptive behavior, children most commonly exhibited defiance (33%) and hyperactivity (29%), followed by inattention (9%), crying (8%), and relational aggression (6%).

Subsequently, children’s peer and object aggression, seeking parent, and disruptive behaviors outside of child control accounted for less than 5% of child codes each. This is consistent with past literature suggesting that young, White children tend to exhibit less severe forms of disruptive behavior (e.g., defiance and hyperactivity, as opposed to aggression; Degnan et al., 2008; Wakschlag et al., 2012). As such, although previous findings have suggested that low-income, ethnic minority children exhibit higher overall frequencies of disruptive behavior (Bradshaw et al., 2010; Harris & Herrington, 2006), the present study extends existing research in that the severity of the behaviors may nonetheless be similar across children from dominant and nondominant ethnic backgrounds.

Frequency of Teachers’ Behavior Management

Findings related to the second and third research questions suggested that teachers frequently used directives (27%), general statements (17%) and questions (14%), as well as moderate amounts of rule-related talk (8%), ignoring child behavior (8%), and statements related to emotions (7%) in response to children’s disruptive behaviors. All other teacher management codes were used infrequently (i.e., less than 6% each), a finding consistent with existing research that posits a high variability in teachers’ behavior management styles (Pianta, La Paro, Payne, Cox, & Bradley, 2002).

Unique differences did emerge, however, regarding which behavior management practices were most often used to control specific forms of disruptive behavior. Teachers were more likely to respond to children’s peer aggression (i.e., a severe form of disruptive behavior) with questions; these questions, in turn, were often paired with statements involving emotions (e.g., children were asked “if they wanted to be first graders or to stay in kindergarten”). This novel finding extends existing

Online Publication of Undergraduate Studies 2017, Volume 8, Issue 2 research involving the use of redirective questions (i.e., asking content-related questions to guide children back to learning tasks). While research has shown such redirective questions to be effective in mitigating more minor forms of disruptive behavior (e.g., inattention; Sutherland, Alder, & Gunter, 2003), problem-focused reflective questions – and particularly questions that emphasize children’s emotions – may be more effective in controlling severe forms of disruptive behavior (e.g., peer aggression) for ethnic minority children.

Furthermore, given its severity, peer aggression was the only child behavior that was never ignored in either classroom; by contrast, and in accordance with existing research and recommended practice (Hester, Hendrickson, & Gable, 2009), teachers often ignored instances of less severe forms of disruptive behavior (e.g., child crying or seeking parent) that are likely maintained by the provision of teacher attention (Bowman, Hardesty, & Mendres-Smith, 2013; Thompson, CotnoirBichelman, McKerchar, Tate, & Dancho, 2007). Teachers’ directives were also the most frequent response to a variety of non-severe disruptive behaviors (e.g., defiance, hyperactivity, inattention, and aggression towards objects), which aligns with existing research that suggests low-income children are more often exposed to directives in the home setting (Hart & Risley, 1995). As such, there may exist some degree of homeschool continuity in the use of behavior management practices, in that teachers are responding to certain forms of disruptive behaviors in ways that are aligned with children’s home cultures.

This is a particularly important finding given recent research that suggests the vast benefits of home-school continuity for supporting children’s later school readiness (Barbarin, Downer, Odom, & Head, 2010; Heath, 1983; Ladd & Dinella, 2009).

Interestingly, teachers in the present study frequently used multiple types of behavior management practices in response to the same instance of disruptive behavior. For example, teachers’ statements involving peers were often paired with directives and statements involving emotions (e.g., “You’re bothering people. Go sit in your chair and play”), whereas statements involving rules were used concurrently with statements involving the logical progression of classroom tasks (e.g., the teacher “told both children that the current time was not for an argument but to clean up as they were told and to move onto circle time”). This is unsurprising given that adults from culturally diverse backgrounds tend to use a combination of recommended and culture-specific management practices to control child behavior (Weinstein et al., 2004). African American and Latino cultures, for instance, emphasize the role of the family or larger community (Roche, Ensminger, & Cherlin, 2007); the reprimands of African American and Latino adults, therefore, may be more likely to manifest as directives that highlight the role of one’s peers and others’ emotions. Similarly, when teachers explicitly replace maladaptive behaviors with adaptive ones (e.g., verbalizing “walk inside the classroom,” as opposed to “no running in the classroom”), associate the role of adaptive behaviors as it relates to what is expected of a child

Teachers’ Responses to Disruptive Behavior

within a given activity setting (Kounin, 1970), and proactively teach logical (e.g., “first finish your juice, then get in line”) and social-emotional (e.g., “inside voices make me really happy”) consequences to child behavior, children are more likely to retain adaptive (Williford & Shelton, 2014) and minimize disruptive (Degol & Bachman, 2015) behaviors in the future.

Management Modifiers

With regards to teachers’ management modifiers, descriptive analyses suggested that the majority of teachers’ management practices were reactive (71%), neutral (61%) or negative (29%), with an equal emphasis on child and behavior.

This finding contrasts existing literature on best practices of classroom management, which highlights the importance of positive (Fuhs et al., 2013) and proactive (Kame’enui & Darch, 1995) management practices, and an emphasis on behavior rather than an emphasis on the child (Clunies-Ross et al., 2008).

Nonetheless, field notes from both classrooms emphasized how teachers successfully controlled their children’s behaviors, thereby suggesting that the management modifiers considered effective with ethnic majority children may differ from those in low-income, ethnically diverse classrooms.

Specifically, the lack of alignment between observed use of management modifiers and the extant literature on best practices may be attributed to differences between the observed classrooms, and the predominantly White, ethnically homogeneous classrooms used in previous research (Gay, 2002). Both teachers, for instance, were situated in relatively large classrooms (i.e., on the upper boundary of the maximum adult-child ratio); an increased class size, in turn, may suggest that teachers in low-income, ethnically diverse classrooms are challenged by more frequent disruptive behaviors than teachers in smaller classrooms with non-minority students (Sheets & Gay, 1996). As a result, teachers in these classrooms may be preoccupied with controlling in-the-moment disruptions as opposed to providing proactive behavioral lessons, thereby explaining why only 7% of management codes were proactive.

Interestingly, and in line with existing research (Clunies-Ross et al., 2008), the use of reactive management practices was also associated with teachers’ use of negative management practices.

Finally, the equal emphasis on child and behavior found in this study suggests that teachers in ethnically diverse classrooms may be using a combination of management practices shown to be effective with European American (i.e., emphasizing children’s behaviors; Fuhs et al., 2013) and ethnic minority (i.e., emphasizing child as individual; Ballegner, 1999) children. And while it is unlikely that teachers would implement management practices that are continuous with the cultural background of every child in the classroom, these initial findings posit that teachers may in fact be harnessing some degree of continuity between the home and school cultures for children in these ethnically diverse classrooms.

Staff Articles & Submissions | 23

Online Publication of Undergraduate Studies 2017, Volume 8, Issue 2 Disruptive Behaviors and Teachers’ Responses: The Role of Child Age

Analyses related to the fourth research question found that disruptive behaviors were more frequent in the preschool classroom. This finding aligns with past research describing that behavioral problems tend to decline with age in accordance with growth in self-regulation skills (Bulotsky-Shearer et al., 2008; Degnan et al., 2008). However, children also undergo rapid socioemotional development during the preschool years, gaining skills in theory of mind (i.e., understanding that individuals have interior mental states), perspective taking, and emotion recognition (e.g., Camras & Allison, 1985; Selman, 1971; Wellman, 2002; Wellman, Cross, & Watson, 2001; Wellman & Liu, 2004). Consequently, age-related differences in socioemotional skills appear to have influenced the specific quality of certain behaviors. For example, instances of relational aggression in the preschool classroom tended to be more selffocused, such as children refusing to share (e.g., “R was playing with some plastic people, but whenever anyone tried to play with them, she would make a small screaming noise and pull the box away from them”), whereas relational aggression in kindergarten was often explicitly directed at others through active teasing (e.g., “T began making fun of Z’s drawing, saying that Z’s picture of Mr. Victor was ‘fat’”). Hence, while the literature has predominantly focused on how the development of socioemotional skills is associated with improved prosocial behavior (e.g., Imuta, Henry, Slaughter, Selcuk, & Ruffman, 2016; Wu & Su, 2014), future research and teacher training should examine how growing socioemotional understanding may similarly contribute to the onset of antisocial and disruptive behaviors (Gomez-Garibello & Talwar, 2015).

Finally, the types of behavior management implemented by teachers also appear to be influenced by developmental changes that occur between the ages of three and six. While the use of management modifiers was consistent across classrooms, statements involving peers, emotions, or logical consequences were more likely to be implemented by kindergarten teachers.

These types of behavior management rely on greater cognitive and socioemotional understanding than directives or rulerelated statements. As such, the use of statements involving peers, emotions or logical consequences may not be as effective for preschoolers given that they are beyond the developmental capacities of children at this age.

Conclusion

In sum, the present study is unique in its naturalistic exploration of the behavior management practices implemented by teachers of low-income, ethnically diverse children, and how these management practices differ in response to specific forms of disruptive behavior. Specifically, this study reveals that teachers in ethnically diverse, low-income classrooms may rely on a combination of behavior management practices to effectively control child behavior (i.e., both culturally-specific and recommended practices); the use of a combination of 24 | Staff Articles & Submissions

Teachers’ Responses to Disruptive Behavior

culture-specific management practices, in turn, ensures that some degree of home-school continuity is present for children in ethnically diverse classrooms. The extant literature, however, has yet to explore how certain forms of disruptive behavior are associated with the presence and extent of home-school continuity or discontinuity in behavior management practices.

In addition, longitudinal research that tracks the behaviors of individual children throughout the early years would also extend findings of the present study by outlining how age-related improvements in children’s classroom behaviors are associated with subsequent changes in teachers’ management practices. The assessment of children’s long-term classroom behaviors vis-à-vis their teachers’ management practices, in turn, could address how teachers’ classroom management practices are also influenced by children’s behaviors (i.e., the bidirectional influence of teachers’ management practices and children’s behaviors; Curby et al., 2014; Wang, Brinkworth, & Eccles, 2013; Williford et al., 2013).

Future studies should therefore investigate the extent to which teachers’ behavior management practices bidirectionally influence the behavioral development of children from lowincome, ethnically diverse backgrounds, in order to better equip researchers, policymakers, and teacher trainers to encourage effective behavior management practices for this at-risk population. In line with research that suggests children learn best when teachers’ classroom management practices take context and cultural differences into account (Weinstein et al., 2004), a more holistic investigation into children’s disruptive classroom behaviors and the existing strategies implemented by teachers of low-income, ethnically diverse children may be a crucial next step in scaffolding the long-term successes of this at-risk population.

References Ballenger, C. (1999). Teaching other people’s children: Literacy

and learning in a bilingual classroom. New York, NY:

Teachers College Press.

Barbarin, O. A., Downer, J., Odom, E., & Head, D. (2010).

Home–school differences in beliefs, support, and

control during public pre-kindergarten and their link

to children’s kindergarten readiness. Early Childhood

Research Quarterly, 25(3), 358-372.

Blair, C. (2010). Stress and the development of self-regulation in context. Child Development Perspectives, 4(3), 181 188.

Blair, C., & Razza, R. P. (2007). Relating effortful control,

executive function, and false belief understanding

to emerging math and literacy ability in kindergarten.

Child Development, 78(2), 647-663.

Bowman, L. G., Hardesty, S. L., & Mendres-Smith, A. E. (2013).

A functional analysis of crying. Journal of Applied

Behavior Analysis, 46(1), 317-321.

Online Publication of Undergraduate Studies 2017, Volume 8, Issue 2 Bradshaw, C. P., Mitchell, M. M., O’Brennan, L. M., & Leaf,

P. J. (2010). Multilevel exploration of factors

contributing to the overrepresentation of Black

students in office disciplinary referrals. Journal of

Educational Psychology, 102(2), 508-520.

Bulotsky-Shearer, R. J., Fantuzzo, J. W., & McDermott, P.

(2008). An investigation of classroom situational

dimension of emotional and behavioral adjustment

and cognitive and social outcomes for Head Start children. Developmental Psychology, 44(1), 139-154.

Camras, L. A., & Allison, K. (1985). Children’s understanding

of emotional facial expressions and verbal labels.

Journal of Nonverbal Behavior, 9(2), 84-94.

Carter, K., & Doyle, W. (2006). Classroom management in

early childhood and elementary classrooms. In

E. Emmer & E. Sabordnie (Eds.), Handbook of

classroom management: Research, practice and

contemporary issues (pp. 373-406). New York, NY: Routledge.

Caughy, M. O. B., & Owen, M. T. (2015). Cultural socialization

and school readiness of African American and

Latino preschoolers. Cultural Diversity and Ethnic

Minority Psychology, 21(3), 391-399.

Clunies‐Ross, P., Little, E., & Kienhuis, M. (2008). Self‐reported

and actual use of proactive and reactive classroom

management strategies and their relationship with

teacher stress and student behaviour. Educational

Psychology, 28(6), 693-710.

Coolahan, K., Fantuzzo, J., Mendez, J., & McDermott, P. (2000).

Preschool peer interactions and readiness to learn:

Relationships between classroom peer play and

learning behaviors and conduct. Journal of Educational

Psychology, 92(3), 458-465.

Curby, T. W., Downer, J. T., & Booren, L. M. (2014). Behavioral

exchanges between teachers and children over

the course of a typical preschool day: Testing

bidirectional associations. Early Childhood Research

Quarterly, 29(2), 193-204.

Dearing, E. (2004). The developmental implications of restrictive

and supportive parenting across neighborhoods

and ethnicities: Exceptions are the rule. Journal of

Applied Developmental Psychology, 25(5), 555-575.

Degnan, K. A., Calkins, S. D., Keane, S. P., & Hill-Soderlund, A.

L. (2008). Profiles of disruptive behavior across early

childhood: Contributions of frustration reactivity,

physiological regulation, and maternal behavior. Child

Development, 79(5), 1357-1376.

Degol, J. L., & Bachman, H. J. (2015). Preschool teachers’

classroom behavioral socialization practices and

low-income children’s self-regulation skills. Early

Childhood Research Quarterly, 31, 89-100.

Delpit, L. D. (2006). Other people’s children: Cultural conflict in

the classroom. New York, NY: The New Press.

Teachers’ Responses to Disruptive Behavior

Duncan, G. J., Dowsett, C. J., Claessens, A., Magnuson, K.,

Huston, A. C., Klebanov, P., ... & Sexton, H. (2007).

School readiness and later achievement. Developmental

Psychology, 43(6), 1428-1464.

Eisenberg, N., Cumberland, A., Spinrad, T. L., Fabes, R. A.,

Shepard, S. A., Reiser, M., ... & Guthrie, I. K. (2001).

The relations of regulation and emotionality to

children’s externalizing and internalizing problem behavior. Child Development, 72(4), 1112-1134.

Emmer, E. T., & Stough, L. M. (2001). Classroom management:

A critical part of educational psychology, with

implications for teacher education. Educational

Psychologist, 36(2), 103-112.

Fuhs, M. W., Farran, D. C., & Nesbitt, K. T. (2013). Preschool

classroom processes as predictors of children’s

cognitive self-regulation skills development. School

Psychology Quarterly, 28(4), 1-13.

Galindo, C., & Fuller, B. (2010). The social competence of Latino

kindergartners and growth in mathematical understanding. Developmental Psychology, 46(3), 579 592.

Garon, N., Bryson, S. E., & Smith, I. M. (2008). Executive

function in preschoolers: A review using an integrative framework. Psychological Bulletin, 134(1), 31-60.

Gay, G. (2002). Preparing for culturally responsive teaching.

Journal of Teacher Education, 53(2), 106-116.

Gay, G. (2006). Connections between classroom management

and culturally responsive teaching. In E. Emmer &

E. Sabordnie (Eds.), Handbook of classroom

management: Research, practice and contemporary issues (pp. 181-222). New York, NY: Routledge.

Gettinger, M. (1988). Methods of proactive classroom management. School Psychology Review, 17, 227-242.

Gomez-Garibello, C., & Talwar, V. (2015). Can you read my

mind? Age as a moderator in the relationship between

theory of mind and relational aggression. International

Journal of Behavioral Development, 39(6), 552-559.

Hamre, B. K., & Pianta, R. C. (2001). Early teacher-child

relationships and the trajectory of children’s school

outcomes through eighth grade. Child Development, 72(2), 625-638.

Harris, D. N., & Herrington, C. D. (2006). Accountability,

standards, and the growing achievement gap: Lessons

from the past half-century. American Journal of

Education, 112(2), 209-238.

Hart, B., & Risley, T. R. (1995). Meaningful differences in the

everyday experience of young American children.

Baltimore, MD: Brookes.

Heath, S. B. (1983). Ways with words: Language, life and work

in communities and classrooms. New York, NY:

Cambridge University Press.

Staff Articles & Submissions | 25

Online Publication of Undergraduate Studies 2017, Volume 8, Issue 2 Hester, P. P., Hendrickson, J. M., & Gable, R. A. (2009). Forty

years later: The value of praise, ignoring, and rules

for preschoolers at risk of disruptive behaviors.

Education and Treatment of Children, 32(4), 513-545.

Howes, C., Burchinal, M., Pianta, R., Bryant, D., Early, D.,

Clifford, R., & Barbarin, O. (2008). Ready to learn?

Children’s pre-academic achievement in pre kindergarten programs. Early Childhood Research

Quarterly, 23(1), 27-50.

Howse, R. B., Lange, G., Farran, D. C., & Boyles, C. D. (2003).

Motivation and self-regulation as predictors of

achievement in economically disadvantaged young children. The Journal of Experimental Education, 71(2), 151-174.

Hoy, A. W., & Weinstein, C. S. (2006). Student and teacher

perspectives on classroom management. In E. Emmer

& E. Sabordnie (Eds.), Handbook of classroom

management: Research, practice and contemporary issues (pp. 181-222). New York, NY: Routledge.

Imuta, K., Henry, J. D., Slaughter, V., Selcuk, B., & Ruffman, T.

(2016). Theory of mind and prosocial behavior in

childhood: A meta-analytic review. Developmental

Psychology, 52(8), 1192-1205.

Jack, S. L., Shores, R. E., Denny, R. K., Gunter, P. L., DeBriere,

T., & DePaepe, P. (1996). An analysis of the

relationship of teachers’ reported use of classroom

management strategies on types of classroom interactions. Journal of Behavioral Education, 6(1), 67-87.

Jordan, N. C., Kaplan, D., Ramineni, C., & Locuniak, M. N.

(2009). Early math matters: Kindergarten number

competence and later mathematics outcomes.

Developmental Psychology, 45(3), 850-867.

Kame’enui, E., & Darch, C. (1995). Managing diverse learners

and classrooms: An instructional classroom

management approach. Columbus, OH: Prentice-Hall.

Koh, M. S., & Shin, S. (2014). A comparative study of

elementary teachers’ beliefs and strategies on

classroom and behavior management in the USA and

Korean school systems. International Journal of

Progressive Education, 10(3), 18-33.

Kounin, J. S. (1970). Discipline and group management in classrooms. New York, NY : Holt, Rinehart & Winston.

Kremer, K. P., Flower, A., Huang, J., & Vaughn, M. G. (2016).

Behavior problems and children’s academic

achievement: A test of growth-curve models with

gender and racial differences. Children and Youth

Services Review, 67, 95-104.

Kunter, M., Baumert, J., & Koller, O. (2007). Effective classroom

management and the development of subject-related interest. Learning and Instruction, 17(5), 494-509.

26 | Staff Articles & Submissions

Teachers’ Responses to Disruptive Behavior

Ladd, G. W., & Dinella, L. M. (2009). Continuity and change in

early school engagement: Predictive of children’s

achievement trajectories from first to eighth grade?

Journal of Educational Psychology, 101(1), 190-209.

Leech, N. L., & Onwuegbuzie, A. J. (2008). Qualitative data

analysis: A compendium of techniques and a

framework for selection for school psychology

research and beyond. School Psychology Quarterly, 23(4), 587-604.

LeFlot, G., van Lier, P. A., Onghena, P., & Colpin, H. (2010).

The role of teacher behavior management in the

development of disruptive behaviors: An intervention

study with the good behavior game. Journal of

Abnormal Child Psychology, 38(6), 869-882.

Li‐Grining, C. P. (2012). The role of cultural factors in the

development of Latino preschoolers’ self‐regulation.

Child Development Perspectives, 6(3), 210-217.

Manke, M. (1997). Classroom power relations: Understanding

student-teacher interaction. New York, NY: Routledge.

Martinez-Pons, M. (2002). Parental influences on children’s

academic self-regulatory development. Theory into

Practice, 41(2), 126-131.

Mashburn, A. J., & Pianta, R. C. (2006). Social relationships and

school readiness. Early Education and Development, 17(1), 151-176.

Mashburn, A. J., Pianta, R. C., Barbarin, O. A., Bryant, D.,

Hamre, B. K., Downer, J. T., … & Howes, C. (2008).

Measures of classroom quality in prekindergarten and

children’s development of academic, language and

social skills. Child Development, 79(3), 732-749.

McClelland, M. M., Cameron, C. E., Connor, C. M., Farris,

C. L., Jewkes, A. M., & Morrison, F. J. (2007). Links

between behavioral regulation and preschoolers’

literacy, vocabulary, and math skills. Developmental

Psychology, 43(4), 947-959.

Merritt, E. G., Wanless, S. B., Rimm-Kaufman, S. E., Cameron,

C., & Peugh, J. L. (2012). The contribution of teachers’

emotional support to children’s social behaviors and

self-regulatory skills in first grade. School Psychology

Review, 41(2), 141-159.

National Center for Education Statistics. (2013). Characteristics

of public and private elementary and secondary schools

in the United States. Available at: https://nces.ed.gov/ fastfacts/display.asp?id=55.

Pianta, R. C., La Paro, K. M., Payne, C., Cox, M. J., & Bradley, R.

(2002). The relation of kindergarten classroom

environment to teacher, family, and school

characteristics and child outcomes. The Elementary

School Journal, 102(3), 225-238.

Pianta, R. C., & Stuhlman, M. W. (2004). Teacher-child

relationships and children’s success in the first years of school. School Psychology Review, 33(3), 444-458.

Online Publication of Undergraduate Studies 2017, Volume 8, Issue 2 Qi, C. H., & Kaiser, A. P. (2003). Behavior problems of

preschoolers from low-income families: Review of the literature. Topics in Early Childhood Special Education, 23(4), 188-216.

Racz, S. J., O’Brennan, L. M., Bradshaw, C. P., & Leaf, P. J. (2016).

The influence of family and teacher factors on early

disruptive school behaviors: A latent profile transition analysis. Journal of Emotional and Behavioral

Disorders, 24(2), 67-81.

Raver, C. C. (2012). Low-income children’s self-regulation in

the classroom: Scientific inquiry for social change.

American Psychologist, 67(8), 681-689.

Raver, C. C., Jones, S. M., Li-Grining, C. P., Metzger, M.,

Champion, K. M., & Sardin, L. (2008). Improving

preschool classroom processes: Preliminary findings

from a randomized trial implemented in Head Start settings. Early Childhood Research Quarterly, 23(1), 10-26.

Razza, R. A., Martin, A., & Brooks-Gunn, J. (2010). Associations

among family environment, sustained attention, and

school readiness for low-income children.

Developmental Psychology, 46(6), 1528-1542.

Razza, R. A., Martin, A., & Brooks-Gunn, J. (2012). The

implications of early attentional regulation for school

success among low-income children. Journal of

Applied Developmental Psychology, 33(6), 311-319.

Rimm-Kaufman, S. E., Curby, T. W., Grimm, K. J., Nathanson,

L., & Brock, L. L. (2009). The contribution of children’s

self-regulation and classroom quality to children’s

adaptive behaviors in the kindergarten classroom.

Developmental Psychology, 45(4), 958-972.

Rimm-Kaufman, S. E., Pianta, R. C., & Cox, M. J. (2000).

Teachers’ judgements of problems in the transition to kindergarten. Early Childhood Research Quarterly, 15(2), 147-166.

Roche, K. M., Ensminger, M. E., & Cherlin, A. J. (2007).

Variations in parenting and adolescent outcomes

among African American and Latino families living in

low-income, urban areas. Journal of Family Issues, 28(7), 882-909.

Scarcella, R. C. (1990). Communication difficulties in second

language production, development, and instruction. In

R. C. Scarcella, E. Andersen, & S. D. Krashen (Eds.),

Developing communicative competence in a second language (pp. 337-352). New York, NY: Newbury.

Selman, R. L. (1971). Taking another’s perspective: Role-taking

development in early childhood. Child Development, 42(6), 1721-1734.

Sheets, R. H., & Gay, G. (1996). Student perceptions of

disciplinary conflict in ethnically diverse classrooms.

Nassp Bulletin, 80(580), 84-94.

Teachers’ Responses to Disruptive Behavior

Snyder, J., Low, S., Schultz, T., Barner, S., Moreno, D., Garst,

M., … & Schrepferman, L. (2011). The impact of brief

teacher training on classroom management and child

behavior in at-risk preschool settings: Mediators and

treatment utility. Journal of Applied Developmental

Psychology, 32(6), 336-345.

Sugai, G., & Horner, R. (2002). The evolution of discipline

practices: School-wide positive behavior supports.

Child and Family Behavior Therapy, 24(1), 23-50.

Sutherland, K. S., Alder, N., & Gunter, P. L. (2011). The effect of

varying rates of opportunities to respond to academic

requests on the classroom behavior of students with EBD. Journal of Emotional and Behavioral Disorders, 11(4), 239-248.

Thompson, R. H., Cotnoir-Bichelman, N. M., McKerchar,

P. M., Tate, T. L., & Dancho, K. A. (2007). Enhancing

early communication through infant sign training.

Journal of Applied Behavior Analysis, 40(1), 15-23.

U.S. Census Bureau. (2016). Poverty status in the last 12 months,

2016 American Community Survey 1-Year Estimates. Retrieved from https://factfinder. census.gov/faces/tableservices/jsf/pages/productview. xhtml?pid=ACS_16_1YR_S1701&prodType=table van Tartwijk, J., & Hammerness, K. (2011). The neglected role

of classroom management in teacher education.

Teaching Education, 22(2), 109-112.

Villegas, A. M., & Lucas, T. (2002). Preparing culturally

responsive teachers: Rethinking the curriculum.

Journal of Teacher Education, 53(1), 20-32.

Vitaro, F., Brendgen, M., Larose, S., & Tremblay, R. E. (2005).

Kindergarten disruptive behaviors, protective factors,

and educational achievement by early adulthood.

Journal of Educational Psychology, 97(4), 617-629.

Wakschlag, L. S., Briggs-Gowan, M. J., Carter, A. S., Hill,

C., Danis, B., Keenan, K., … & Leventhal, B. L. (2007).

A developmental framework for distinguishing

disruptive behavior from normative misbehavior in

preschool children. Journal of Child Psychology and

Psychiatry, 48(10), 976-987.

Wakschlag, L. S., Choi, S. W., Carter, A. S., Hullsiek, H., Burns,

J., McCarthy, K., … & Briggs-Gowan, M. J. (2012).

Defining the developmental parameters of temper

loss in early childhood: Implications for developmental psychopathology. Journal of Child Psychology and

Psychiatry, 53(11), 1099-1108.

Wallace, T. L., Sung, H. C., & Williams, J. D. (2014). The defining

features of teacher talk with autonomy-supportive

classroom management. Teaching and Teacher

Education, 42, 34-46.

Wang, M. T., Brinkworth, M., & Eccles, J. (2013). Moderating

effects of teacher–student relationship in adolescent

trajectories of emotional and behavioral adjustment.

Developmental Psychology, 49(4), 690-705.

Staff Articles & Submissions | 27

Online Publication of Undergraduate Studies 2017, Volume 8, Issue 2 Wanless, S. B., McClelland, M. M., Tominey, S. L., & Acok, A. C.

(2011). The influence of demographic risk factors

on children’s behavioral regulation in prekindergarten

and kindergarten. Early Education & Development, 22(3), 461-488.

Webster‐Stratton, C., Reid, M. J., & Stoolmiller, M. (2008).

Preventing conduct problems and improving school

readiness: Evaluation of the Incredible Years teacher

and child training programs in high-risk schools.

Journal of Child Psychology and Psychiatry, 49(5), 471-488.

Weinstein, C. S., Tomlinson-Clarke, S., & Curran, M. (2004).

Toward a conception of culturally responsive classroom management. Journal of Teacher Education, 55(1), 25 38.

Wellman, H. M. (2002). Understanding the psychological world:

Developing a theory of mind. In U. Goswami (Ed.),

Handbook of childhood cognitive development (pp.

167-187). Oxford: Blackwell.

Wellman, H. M., Cross, D., & Watson, J. (2001). Meta-analysis of

theory-of-mind development: The truth about false belief. Child Development, 72(3), 655-684.

Wellman, H. M., & Liu, D. (2004). Scaling theory-of-mind tasks.

Child Development, 75(2), 523-541.

Williford, A. P., & Shelton, T. L. (2014). Behavior management

for preschool-aged children. Child and Adolescent

Psychiatric Clinics, 23(4), 717-730.

Williford, A. P., Maier, M. F., Downer, J. T., Pianta, R. C., &

Howes, C. (2013). Understanding how children’s

engagement and teachers’ interactions combine to

predict school readiness. Journal of Applied

Developmental Psychology, 34(6), 299-309.

Willoughby, M., Kupersmidt, J., Voegler-Lee, M., & Bryant,

D. (2011). Contributions of hot and cool self regulation to preschool disruptive behavior and

academic achievement. Developmental

Neuropsychology, 36(2), 162-180.

Wu, Z., & Su, Y. (2014). How do preschoolers’ sharing beliefs

relate to their theory of mind understanding? Journal

of Experimental Child Psychology, 120, 73-86.

Wubbels, T. (2011). An international perspective on classroom

management: What should prospective teachers learn?

Teaching Education, 22(2), 113-131.

Yates, G. C. R., & Yates, S. M. (1990). Teacher effectiveness

research: Towards describing user-friendly classroom instruction. Educational Psychology, 10(3), 225-238.

Zimmerman, B. J. (1998). Developing self-fulfilling cycles of

academic regulation: An analysis of exemplary

instructional models. In D. H. Schunk & B. J.

Zimmerman (Eds.), Self-regulated learning: From

teaching to self-reflective practice (pp. 1-19). New

York, NY: Guilford.

28 | Staff Articles & Submissions

Teachers’ Responses to Disruptive Behavior

Online Publication of Undergraduate Studies 2017, Volume 8, Issue 2

Teachers’ Responses to Disruptive Behavior Appendix Coding Scheme

Staff Articles & Submissions | 29

BIOGRAP

30

HIES

31

Julius A. Utama Editor-in-Chief jau228@nyu.edu

Julius Utama is a senior in the Applied Psychology program with a minor in Sociology. He is a research assistant on the NYU L-FELD team, led by Dr. Gigliana Melzi and Dr. Adina Schick, and is in the process of completing an honors thesis investigating the role of home-school continuity in behavior management practices on the self-regulation skills of Latino preschoolers.

Julius is also a research assistant in Dr. Lisa Suzuki’s Emotional Intelligence lab, where he has conducted several independent research projects examining the association between emotional and cultural intelligence, the mediating role of ethnic identity, and the creation and validation of the Digital Emotional Intelligence index (DEQ). Julius presented two posters at the 125th annual American Psychological Association (APA) Convention, and has previously worked as a research assistant for the Centre for Strategic and International Studies (CSIS) in Jakarta, Indonesia. Julius hopes to expand his involvement in analytics and big data as he transitions into a market research role post-graduation.

32 | Biographies

Elysha Clark-Whitney Editor-in-Chief ecw330@nyu.edu

Elysha Clark-Whitney is a senior in the Applied Psychology undergraduate program, with a minor in history. Her primary area of interest is Autism Spectrum Disorder. She has had the opportunity to work with children on the Autism spectrum through volunteering at LearningSpring School and an internship conducting Applied Behavior Analysis (ABA) at the Manhattan Children’s Center.

She is particularly interested in researching the applications of ABA to the treatment of compulsions and repetitive behaviors among children on the Autism spectrum, and is in the process of becoming certified as a Registered Behavior Technician in order to practice ABA. Elysha also works with preschoolers from families of low socioeconomic status, as part of her work with the NYU L-FELD research team, and is also a research assistant in the NYU FACES Lab. Elysha is currently working on an honors thesis about the relation between expressive language, executive function and narrative skills in low-income bilingual preschoolers.

Alyce Cho

Sophia Meifang Wang

Alyce Cho is a junior majoring in Applied Psychology with a minor in Urban and Global Education Studies. Her primary area of interest is Special Education Policy, and she has previously worked with children. Alyce has also worked in a law office in Los Angeles, and is currently preparing for law school.

Sophia Wang is a Sophomore in the Applied Psychology and Global Public Health program.

She is also pursuing a minor in Web Programming and Applications. She is currently a research assistant in the Social Inequalities and Intergroup Relations Lab. She is also a research assistant for the Chinese Families Lab. Additionally, she served as an Orientation Leader for the past semester.

She is interested in using different research methods to inform better decisions in design.

Programming & Communications Director ac5843@nyu.edu

Layout & Design Director sophia.m.wang@nyu.edu

Biographies | 33

Christina Ducat | Contributing Writer crd368@nyu.edu Christina Ducat is a senior in the Applied Psychology & Global Public Health program. Additionally, she is majoring in Politics, focusing on international politics and human rights. She has worked with the ROSES Advocacy Program since the fall of 2016, collaborating with youth who have been involved with the juvenile justice system to connect them to community resources and help them advocate on their own behalf.

Peter Goldie | Contributing Writer pdg283@nyu.edu Peter Goldie is a junior in the Applied Psychology undergraduate program with a minor in Sociology. Through his work at Kurtz Psychology Consulting, he is learning about clinical skills utilized with children who have selective mutism and/or oppositional defiant disorder. He is also a research assistant with INSIGHTS, working on collecting follow-up data from the project’s socio-emotional learning intervention. Peter is interested in graduate programs in clinical/counseling psychology.

Ali Swoish | Contributing Writer ans521@nyu.edu

34 | Biographies

Ali Swoish is a senior in the Applied Psychology program. She currently works as a Psychosocial Core Teacher at the Quad Manhattan, a preparatory after-school program for Twice Exceptional children. She also works at the Nordoff-Robbins Center for Music Therapy, filming and observing music therapy sessions. She is working on an independent research project, studying how music engagement is influenced by various music therapy methods in musically gifted individuals.

Ali also maintains a strong presence in the creative arts as a dancer, choreographer, and current President of NYU Pulse Dance Project. In the future, she hopes to utilize her interest in movement and experience with creative arts therapies to pursue clinical work with children and adolescents.

Samantha Valley | Staff Writer smv293@nyu.edu Samantha Valley is a senior in the Applied Psychology program.

She is an advanced counselor aide for the Employment Program for Recovered Alcoholics, Inc., where she assists recovered addicts in exploring and assessing their own personal vocational goals and interests. Her passion for research has led to her investigation of addiction across populations and substances, with a particular focus on the United States’ heroin epidemic.

She hopes to further her career in psychological research and to eventually pursue a PhD in Addiction Psychology. She aspires to contribute to the growing platform of addiction awareness, and to create and implement various intervention programs for teens and adolescents in order to minimize the growing rates of addiction across the United States.

Biographies | 35