MUMJ Volume 20, Issue 1 (2023)

Page 1

McMaster University Medical Journal

Editorial Board 2022-23

CATHERINE ANDRARY

SAPRIYA BIRK

DOROTA BOROVSKY

Editors-in-Chief

KEVIN KIM AND ALI ZHANG

Executive Editors

HARGUN KAUR AND JIM XI

Submission Editors

FELICIA CEBAN

EVAN FANG

SHAHZAIB KHATTAK

Reviewers

LYNAEA KOROL-FILBEY

JUSTINE LAU

REBECCA WONG

CATHERINE ANDARY

TARA BEHROOZIAN

SAPRIYA BIRK

CHRISTOPHER BRINTON

FELICIA CEBAN

EVAN FANG

NIKHIL HARIHARAN

SAPNA HUMAR

LYNAEA KOROL-FILBEY

ASHLEY KWON

Cover Art

VITORIA OLYNTHO

JUSTINE LAU

JONAH RAKOFF

JIAN ROUSHANI

JOE STEINMAN

AUSTINE WANG

i __________________________________________________________

TABLE OF CONTENTS

LETTER FROM THE EDITORS………………………………………………………………iii

KEVIN KIM AND ALI ZHANG

COVER ARTIST STATEMENT………………………………………………………………...iv

VITORIA OLYNTHO

ORIGINAL RESEARCH ARTICLES

GENDER DIFFERENCES IN PATIENTS WITH TRAUMATIC BRAIN INJURY: A RETROSPECTIVE ANALYSIS………………………………………………………………….1

JEFFREY LAM SHIN CHEUNG, HAJER NAKUA, ANIL DOSAJ, ET AL.

WEIGHT BEFORE YOU JUDGE: INVESTIGATING PREVALENCE, MANIFESTATIONS AND CHANGES IN WEIGHT BIAS ATTITUDES TOWARDS MEDICAL EDUCATION…22

MEENA SAAD, MARINA SAAD, ET AL.

COMMENTARIES

REDUCING HARM FROM THE CLOUD: INTERNET BASED COGNITIVE BEHAVIOURAL THERAPY FOR OPIOID USE DISORDER………………………………..14

BOWEN MA AND WADEED IRFAN

CERVICAL CANCER SCREENING IN TRANSGENDER MEN AND NON-BINARY PEOPLE WITH A CERVIX …………………………………………………………………….40

TESSA ANZAI, AMANDA SELK, JULIE MY VAN NGUYEN

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From the Editors

McMaster University Medical Journal, Volume 20

Editors-in-Chief

With the 20th volume, McMaster University Medical Journal celebrates its 20th year of showcasing the research conducted by medical and graduate students from McMaster University and other institutions around the world. MUMJ’s mission has been to share diverse research and thought-provoking opinions on the rapidly changing landscape of health care. The 20th volume is no different and still committed to this mission.

The 20th volume continues to present the unique works of medical and graduate students. In realm of medical education, articles ranging from COVID-19’s effect on medical student training in radiology to investigating weight bias attitudes provide perspective to known obstacles in medical training. One author explored the ever contentious issues of unmatched medical student through the CaRMs residency matching process through an economic lens, examining how budget constraints in applying to residency programs affects the underlying algorism and applicants’ chance of matching. Multiple authors’ articles also examined long-standing health inequities as they explored cervical cancer screening in transgender and non-binary patients, effects of providing underprivileged students with information about careers in healthcare, and more.

Editor-in-chiefs’ have developed a habit in acknowledging the immense individuals on the editorial board that has kept MUMJ going for the past 20 years. Again, this year is no different! There is no way MUMJ could exist without our executive editors, submission editors, and reviewers who volunteer their precious time to bring every issue to life. We are amazed by our team as we witness the detailed critiques, comments by our editors, and discussions authors have with the editorial team.

Last but certainly not least, we want to thank our readers. With an ever increasing body of literature (thank you internet, technology, and… ChatGPT?), it is inevitable we are increasingly selective with the journals we choose to read. Like all craft beer, MUMJ is a continuous work in progress that may not satisfy your cravings, but is always put together with love.

Sincerely,

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Cover Art

“Murine Decidual-Placental Interface”

Artist Statement

“Murine Decidual-Placental Interface” is an immunofluorescence confocal microscopy image of the placenta of a pregnant mouse. The placenta is an essential site for nutrient exchange, serving as the point of direct contact between the mother and the fetus. It is essential to promote growth and provide nourishment to the fetus but also to shield it from immune-mediated injury.

The decidua can be seen towards the top of the image, where maternal blood vessels (green circles) supply blood and nutrients to the placenta. Natural killer, or NK cells, seen in red comprise around two-thirds of all the maternal cells within the decidua. In a healthy pregnancy, these cells form a microenvironment to promote tissue growth and remodelling. An extensive network of vessels seen in blue supplies blood from the placenta to the fetus. The amniotic sac in lime green encloses the fetus, localized toward the lower portion of the image.

The image was acquired on a Leica Stellaris 5 microscope using a 40x/0.95 air-immersed objective. Purple: Nuclei (DAPI); Green: alpha-smooth muscle actin; Red: NK cells (DBA); Lime green: EpCAM; Blue: Syndecan 1 (CD138).

Artist Bio

Vitoria is a fourth-year student in the Bachelor of Health Sciences program at McMaster University. She moved from Brazil to Canada in 2018 to pursue a career in biological research and began working with Dr. Joshua Koenig at the McMaster Immunology Research Centre in 2022. Her current research project involves developing a multiplexed immunofluorescence imaging platform to investigate the cell microenvironment of human and mouse tissues.

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Original Research Article

Gender differences in patients with traumatic brain injury: A retrospective analysis

1Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada

2Institute of Medical Science, University of Toronto, Toronto, Ontario, Canada

3St. Michael’s Hospital, Toronto, Ontario, Canada

4University of Guelph-Humber, Etobicoke, Ontario, Canada

Abstract

Background: Inrecent years, the incidence of traumatic brain injury (TBI) in Canada has doubled, with females having higher prevalence. Current literature lacks consensus regarding how gender influences post-TBI outcomes, prompting further investigation.

Aims: To study whether gender impacts post-TBI outcomes with a focus on psychiatric-related outcomes.

Methods: A retrospective cohort study of patients admitted to St. Michael’s Hospital for TBI. Using health consultation reports, we collected patient demographic characteristics, cause of TBI, past medical history, diagnoses following TBI, and treatments. All measures were qualitative and coded as no or yes (e.g. suffered from depression: no or yes). Chi-square tests were used to assess whether males and females had differing TBI outcomes. Multiple comparisons were corrected for using the Bonferroni Correction.

Results: Data were collected and analyzed for 39 patients (23 females) (mean age = 38.5 ± 12.7 years). The causes of TBI included 16 (41.0%) motor vehicle accidents, 8 (20.5%) pedestrian accidents, 3 (7.7%) bicycle accidents, 10 (25.6%) cases of falls, 5 (12.8%) cases of physical assaults, and 3 (7.7%) sports-related injuries. Long-term disabilities resulting from TBI occurred in 14 patients (35.9%). Females were significantly more likely to experience orthopedic issues resulting from TBI, compared to males (X2 = 5.35, p = 0.021), but this significance did not make it past multiple comparison correction. No other significant differences were noted.

Conclusions: We did not find better post-TBI outcomes in either gender in this pilot retrospective analysis. A larger sample and quantitative data are necessary to substantiate the findings.

Keywords: traumatic brain injury, gender comparison, quality of life

Corresponding author: Shree.Bhalerao@unityhealth.to

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, Shweta , ,

Introduction

Traumatic brain injury (TBI) is the leading cause of morbidity and under the age of 45 worldwide (1) The incidence of TBI in Canada has increased with an annual percent increase of 9.6% (2), and approximately 506.4 per 100,000 people in the United States experience TBI annually (3).

Consequences of TBI include alteration to the brain structure, psychiatric complications, and decreased quality of life (4) Patients with TBI experience poorer executive functioning skills, such as delayed reaction time and lower accuracy; altered structural neural networks (5); and greater memory deficits (6, 7) They also experience increased atrophy in the hippocampus (8, 9); abnormalities in white matter microstructure, such as lower fractional anisotropy (10, 11, 12, 13); and long-term global structural alterations (9).

Though males are 40% more likely to experience a TBI compared to females (14), the rate of female TBI events has risen significantly in recent years (15, 16). These developments have prompted further research into the potential effects of sex in the trajectory of TBI and resulting long-term disability. Beyond differences in incidence, the trajectory of rehabilitation and the likelihood of disability (mental and physical) has also differed between the sexes (17, 18) However, these results remain inconclusive as some reports suggest that females show worse outcomes (19, 20), whereas other reports suggest the opposite (17, 18, 21) Amid these conflicting findings, few studies have considered the potential effect of gender, as a social construct, on psychiatric-related post-TBI outcomes. Furthermore, though a population-based cohort study found that the incidence rate of psychiatric disorders was two times higher in patients who suffered a TBI compared to patients who did not (22), long-term psychiatric health implications have not been widely studied in this population and thus require further investigation.

Using retrospective clinical data from a large head injury clinic, this pilot study aimed to explore gender-related differences post-TBI and psychiatric health outcomes. One primary outcome of interest was the diagnosis of a psychiatric disorder post-TBI and exploring the impact of gender. We hypothesized that TBI outcomes would differ significantly and that females would have a better quality of life and fewer psychiatric complications post-TBI based on commonly reported findings that males suffer more severe forms of TBI (17, 18).

Methods

Subjects and recruitment

We performed a retrospective analysis of patients who were admitted for a TBI at the St. Michael’s Hospital Head Injury Clinic between January 2016 and July 2016 inclusively. The study protocol was approved by the St. Michael’s Hospital Research Ethics Board (#16-220). As per article 3.7 of the Tri-Council Policy Statement, patient consent was not required due to the minimal risk to participants (23).

We examined the records of 100 patients from an existing database at the Head Injury Clinic. A total of 50 self-identified male and 50 self-identified female patients who were referred to the lead investigator in the clinic, following mild to moderate head trauma were assessed for suitability of inclusion. The only inclusion criteria were the presence of TBI, defined as 1) experiencing an episode of physical trauma; 2) loss of consciousness or altered level of consciousness defined as a Glasgow coma scale of <15; and 3) having post-traumatic amnesia for an extended period of time (>72 hours). There were no exclusion criteria applied to patients.

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Data collection

We reviewed health consultation reports for patients at their initial clinical encounter for TBI and up to 6 months afterward. We collected the following baseline information from patients: patient self-identified gender (male or female); patient biological sex (male or female); cause of TBI; demographic characteristics; past psychiatric disorders and symptoms; past non-psychiatric conditions;familypsychiatrichistory;past medicalhistory;developmentalhistory;andlegalstatus history.

For post-TBI outcomes, we collected data for the following variables, which were identified a priori through a literature review assessing common variables considered in gender difference studies following traumatic injury: mini-mental status exam (MMSE) results; organ system damage (such as kidney and liver failure); psychiatric disorders as diagnosed by DSM IV criteria; patient stressors; support systems; and prescribed treatment regimens. Disability status due to TBI, if present, was categorized as either short term (<3 months) or long term (>3 months). Due to the qualitative nature of the data, variables were coded as no (0) or yes (1) (e.g. did the patient experience depression: no or yes).

Data analysis

To assess the dichotomous data, we used chi-square tests to determine whether males and females differed in the variables listed above. Multiple comparisons were corrected for using a Bonferroni approach.(24) All analyses were performed in R (version 3.5.0)(25) and all p-values were 2-sided and considered significant at less than 0.05.

Results

In our pilot analysis, we collected data from 39 patients (age range: 18-73 years; mean = 38.5 ± 12.7 years; median = 38 years). Of these patients, 16 (41.0%) identified as male and 23 (59.0%) identified as female. The biological sex matched the patients’ self-reported gender in all cases (100.0%). There were no significant differences between males and females at baseline in terms of post-secondary education status nor past psychiatric history (Table 1). Data suggested that more womenexperienced orthopedic injury(such asfracturesanddislocations)following TBI,a p-value of 0.021.

Causes of traumatic brain injury

Among the 39 patients, the causes of TBI included 16 (41.0%) motor vehicle accidents, 8 (20.5%) pedestrian accidents, 3 (7.7%) bicycle accidents, 10 (25.6%) cases of falls, 5 (12.8%) cases of physical assaults, and 3 (7.7%) sports-related injuries. The causes of TBI were not mutually exclusive for a given patient, thus multiple causes may have been applied for a single patient. There were no significant differences in the causes of TBI between male and female patients (Figure 1).

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Males (%) (N = 16) Females (%) (N = 23) X2 P Obtained post-secondary education 10 (62.50) 15 (65.22) 0.030 0.862 Presence of past psychiatric history 9 (56.25) 5 (21.74) 0.255 0.614 Past psychiatric admission(s) 6 (37.50) 3 (13.04) 0.286 0.593 History of suicide attempt(s) in past 1 (6.25) 2 (8.70) 0.883 0.347 Currently seeing a psychiatrist 7 (43.75) 7 (30.43) 0.727 0.394 Taking antidepressants 8 (50.00) 7 (30.43) 1.472 0.225 Taking antipsychotics 0 (0.00) 1 (4.35) 1.475 0.225
Table 1. Baseline patient characteristics Figure 1. Total number of causes of traumatic brain injury according to patient gender (16 males, 23 females).

Gender differences in post-traumatic brain injury outcomes

With gender set as the independent variable, the only significant difference noted was that females were more likely to experience orthopedic injury resulting from their TBI when compared to males (X2 = 5.35, p = 0.021). However, this significance did not surpass the comparison threshold after correcting for multiple comparisons. There were no other significant differences regarding disability status, organ system damage, or prescribed treatments between males and females in this sample (Table 2). Likewise, there were no significant differences between males and females in post-TBI psychiatric disorders, post-TBI psychiatric symptoms, or post-TBI mental status exam results (Table 3).

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Males (%) (N = 16) Females (%) (N = 23) X2 P Disability status Long term disability 1 (6.25) 4 (17.39) 1.048 0.306 Short term disability 1 (6.25) 1 (4.35) 0.070 0.791 Organ system damage Cardiac injury 0 (0.00) 1 (4.35) 0.714 0.398 Respiratory injury 1 (6.25) 0 (0.00) 1.475 0.225 Brain trauma 14 (87.50) 23 (100.00) 3.030 0.082 Orthopedic injury 1 (6.25) 9 (39.13) 5.350 0.021 Prescribed treatment Physiotherapy 2 (12.50) 0 (0.00) 3.030 0.082 Speech pathology 0 (0.00) 0 (0.00) 0.070 0.791 Massage therapy 1 (6.25) 1 (4.35) 0.070 0.791 Medications 14 (87.50) 20 (86.96) 1.927 0.165 Psychological CBT 0 (0.00) 1 (4.35) 0.002 0.960 Mindfulness 2 (12.50) 3 (13.04) 0.714 0.398 Sleep hygiene 10 (62.50) 20 (86.96) 0.002 0.960
Table 2. Differences in general outcomes between males and females following traumatic brain injury
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Males (%) (N = 16) Females (%) (N = 23) X2 P Psychiatric disorders Depression 12 (75.00) 16 (69.57) 0.138 0.711 Anxiety 8 (50.00) 11 (47.83) 0.018 0.894 Psychosis 2 (12.50) 0 (0.00) 3.030 0.082 Neurocognitive disorder 4 (25.00) 4 (17.39) 0.335 0.563 Substance abuse 2 (12.50) 0 (0.00) 3.030 0.082 Alcohol abuse 3 (18.75) 2 (8.70) 0.853 0.356 Impulsivity 3 (18.75) 1 (4.35) 2.126 0.145 Anger/aggression 5 (31.25) 4 (17.39) 1.021 0.312 Irritability 1 (6.25) 1 (4.35) 0.070 0.791 Phobia 1 (6.25) 0 (0.00) 1.475 0.225 Panic attacks 1 (6.25) 0 (0.00) 1.475 0.225 PTSD 4 (25.00) 8 (34.78) 0.424 0.515 Psychiatric symptoms Sleeping problems 2 (12.50) 9 (39.13) 3.305 0.069 Loss of consciousness 7 (43.75) 11 (47.83) 0.005 0.944 Altered consciousness 3 (18.75) 8 (34.78) 0.965 0.326 Post traumatic amnesia 7 (43.75) 15 (65.22) 1.282 0.258 Seizure 0 (0.00) 1 (4.35) 0.670 0.413 Tremor 1 (6.25) 1 (4.35) 0.098 0.754 Loss/change in sense of smell 2 (12.50) 2 (8.70) 0.207 0.649 Loss/change in sense of taste 3 (18.75) 3 (13.04) 0.330 0.565 Loss/change in vision 5 (31.25) 7 (30.43) 0.111 0.739 Vertigo 5 (31.25) 3 (13.04) 2.249 0.134 Vestibular balance problems 1 (6.25) 3 (13.04) 0.392 0.531 Persistent Pain 2 (12.50) 8 (34.78) 2.154 0.142 Brain surgery 1 (6.25) 2 (8.70) 0.051 0.821 Memory changes 8 (50.00) 9 (39.13) 0.741 0.389 Attentional changes 4 (25.00) 7 (30.43) 0.063 0.802 Language Speech changes 3 (18.75) 4 (17.39) 0.041 0.839 Executive function changes 2 (12.50) 0 (0.00) 3.237 0.072 Problems with visuospatial skills 0 (0.00) 1 (4.35) 0.701 0.403
Table 3. Differences in psychiatric outcomes between males and females following traumatic brain injury

Discussion

Based on the current literature, we hypothesized that the TBI outcomes would differ significantly between males and females with females having a better quality of life and fewer psychiatric complications. However, we demonstrated that there were no significant differences in post-TBI outcomes, severity, and psychiatric diagnoses between male and female patients. We did note an increase in orthopedic-related injuries in female patients that was insignificant after correcting for multiple comparisons. Previous studies have correlated orthopedic injuries with lower estrogen levels in post-menopausal women (26)

Animal studies have been used to generate hypotheses for the potential impact of sex on post-TBI outcomes. In particular, some research suggests that estrogen and progesterone have neuroprotective and neurogenerative effects on TBI which may explain the lower severity of TBI in female mice (27, 28). Animal studies also found that mice administered with progesterone experienced less DNA fragmentation, cell apoptosis, edema and neuronal degeneration following injury (29, 30). Estrogen has demonstrated neuroprotective effects by acting as a lipid antioxidant; increasing N-methyl-D-aspartate glutamate receptor response; preventing dopamine loss following brain injury; and increasing cerebral blood flow, among other mechanisms (31, 32). As such, researchers have postulated that female humans may have better recovery and outcomes following injuries compared to males.

Human studies on the effects of gender on post-TBI outcomes have yielded inconsistent results. Some reports suggested that females were more likely to resume work and had a shorter average post-traumatic amnesia duration post-TBI compared to males (17). However, more recent studies have found contrasting results suggesting that males have higher rates of improved outcomes (33, 34). These discrepancies may be partially explained by methodological and sample size differences. Studies with smaller samples generally had an increased likelihood of concluding that females experienced worse post-TBI outcomes (35) Overall, few studies have explicitly considered the potential influence of gender on post-TBI outcomes from a psychiatric-focused perspective.

MUMJ Vol. 20 No. 1, pp. 1–13 August 2023 7 Mini-mental status exam Psychomotor retardation 3 (18.75) 7 (30.43) 0.676 0.411 Speech 8 (50.00) 7 (30.43) 1.526 0.217 Mood: good/okay/bad 8 okay (50.00) 8 bad (50.00) 14 okay (60.87) 9 bad (39.13) 4.852 0.303 Euthymic 1 (6.25) 4 (17.39) 1.048 0.306 Dysphoric 7 (43.75) 11 (47.83) 0.063 0.802 Impaired cognition 1 (6.25) 3 (13.04) 0.473 0.492 Impaired memory 9 (56.25) 13 (56.52) 0.000 0.987 Impaired attention 7 (43.75) 8 (34.78) 0.321 0.571 Impaired processing speed 11 (68.75) 13 (56.52) 0.596 0.440 Impaired executive function 2 (12.50) 2 (8.70) 0.148 0.700 Visuospatial problems 1 (6.25) 2 (8.70) 0.079 0.778

Comparison with the literature

Our sample’s injury results mirrored other studies, with the most common cause of TBI being motor vehicle accidents, followed by falls, pedestrian accidents, physical assault, bicycle accidents, and sports-related injuries (36, 37, 38, 39, 40) Although there were gender differences in the cause of TBI, with female patients having a higher incidence of motor vehicle accidents, pedestrian accidents, and sports-related injuries and males having a higher incidence of bicycle accidentsandphysicalassault,therewerenostatisticallysignificantdifferenceswhichisconsistent with some previous findings (36) but contrasts others (37). Discrepancies in the causes of TBI between this current study and previous studies may be partially attributed to different sample sizes, geographic locations (41), and patient characteristics such as age (42).

Our primary outcome of interest was psychiatric disorders diagnosed following an episode of TBI. These included depression, anxiety (43), personality changes, cognitive decline, and psychosis (4). Females in our dataset were more likely to receive a diagnosis of depression, anxiety, and PTSD, but this was not significant, coinciding with some previous reports (44, 45). Yet,otherstudieshave shownsignificantdifferences inpsychiatricoutcomesand have evenshown that women are at a higher risk of developing anxiety and depression following a TBI event (46, 47, 48). This social factor supports the multifaceted connection, which may extend beyond hormonal biology, between gender and outcomes following TBI events. Other social factors such as the age of the patient at the time of their first TBI (49, 50) and stress levels in their day to day life (51) can also support the multifaceted connection potentially contributing to post-TBI psychiatric outcomes.

We also examined differences between males and females regarding MMSE scores and once again found no significant differences between the two genders. As most studies that have considered the MMSE in the context of TBI have focused on assessing its predictive value for further complications rather than differences due to gender or sex, there is limited data available to compare our findings.

Clinical implications

Though our pilot data should be interpreted with caution, our findings suggest that post-TBI outcomes are not significantly influenced by gender, and thus patients should not be treated differently following TBI based on their gender alone. This coincides with several TBI treatment guidelines that do not support different treatments based on patient gender or sex (52, 53, 54). Alternatively, tailoring treatment strategies to specific patient needs and evaluating each scenario on a case-by-case basis may be preferable in optimizing TBI care and patient outcomes (52)

Strengths and limitations

Our study’s primary strength is the extensive amount of information collected on patients at baseline and following TBI regarding post-TBI psychiatric conditions and symptoms, whereas previous studies have generally been limited to assessing symptoms of depression, post-traumatic stress disorder, and anxiety (20, 45, 46, 55) Furthermore, we obtained patient biological sex and self-reported gender from the existing database. Previous studies have often failed to distinguish between these terms which may differ greatly as one represents patient biology whereas the other

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considers a social construct. Thus, our findings may apply to both sex and gender comparison studies in the field of TBI recovery.

Our study has several weaknesses. The small sample size provided limited power for our analyses and increased the possibility of false negatives. As this study was a pilot study using a convenience sample to determine the feasibility of a larger trial, a larger sample size would better represent the outcomes of TBI in the general population. Therefore, future studies would benefit from increasing the sample size, such as by pooling results in a multi-center study, to increase the power of analyses. This may also allow for the possibility of a multivariate analysis and age-based stratificationofresultsto exploreoutcomesinpre-vs post-menopausal patients Another limitation was that our pilot study aimed to identify areas for further investigation, and thus our data was exclusively dichotomous, rendering it difficult to evaluate the severity or duration of psychiatric symptoms. For instance, we found that more females reported sleeping problems than males postTBI but could not evaluate the differences in sleep quality, duration of symptoms, or impact on patient quality of life. Another limitation is that while we were able to account for past psychiatric history (Table 1), it is possible that other variables that were not accounted for, such as the severity of TBI and social support, may have impacted the chances of diagnosis with a psychiatric disorder. In the future, we plan to address this limitation by collecting qualitative and quantitative measures for patient symptoms where applicable.

Conclusion

Overall, our pilot study data does not support the notion that there are significant differences in post-TBI outcomes due to gender, specifically with regards to psychiatric wellbeing. Considering thelimitedsampleof thispilotstudy, alargerpopulationandthe incorporationof morequantitative data may help to substantiate findings.

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31. Stein DG, Hoffman SW. Estrogen and progesterone as neuroprotective agents in the treatment of acute brain injuries. Pediatr Rehabil. 2003;6(1):13-22.

32. O'Connor CA, Cernak I, Vink R. Both estrogen and progesterone attenuate edema formation following diffuse traumatic brain injury in rats. Brain Res. 2005;1062(1-2):171-4.

33. Hu XB, Feng Z, Fan YC, Xiong ZY, Huang QW. Health-related quality-of-life after traumatic brain injury: a 2-year follow-up study in Wuhan, China. Brain injury. 2012;26(2).

34. Ahman S, Saveman BI, Styrke J, Björnstig U, Stålnacke BM. Long-term follow-up of patients with mild traumatic brain injury: a mixed-method study. Journal of rehabilitation medicine. 2013;45(8).

35. Gupte R, Brooks W, Vukas R, Pierce J, Harris J. Sex Differences in Traumatic Brain Injury: What We Know and What We Should Know. Journal of neurotrauma. 2019;36(22).

36. Covassin T, Bay E. Are there gender differences in cognitive function, chronic stress, and neurobehavioral symptoms after mild-to-moderate traumatic brain injury? The Journal of neuroscience nursing : journal of the American Association of Neuroscience Nurses. 2012;44(3).

37. Bazarian JJ, Blyth B, Mookerjee S, He H, McDermott MP. Sex differences in outcome after mild traumatic brain injury. Journal of neurotrauma. 2010;27(3).

38. Kadyan V, Mysiw WJ, Bogner JA, Corrigan JD, Fugate LP, Clinchot DM. Gender differences in agitation after traumatic brain injury. American journal of physical medicine & rehabilitation. 2004;83(10).

39. Herrera-Melero MC, Egea-Guerrero JJ, Vilches-Arenas A, Rincón-Ferrari MD, FloresCordero JM, León-Carrión J, et al. Acute predictors for mortality after severe TBI in Spain: Gender differences and clinical data. Brain injury. 2015;29(12).

40. Donders J,Hoffman NM.Gender differences in learning and memory after pediatric traumatic brain injury. Neuropsychology. 2002;16(4).

41. Al-Habib A, A-Shail A, Alaqeel A, Zamakhshary M, Al-Bedah K, Alqunai M, et al. Causes and patterns of adult traumatic head injuries in Saudi Arabia: implications for injury prevention. Annals of Saudi medicine. 2013;33(4).

42. Biswas R, Kabir E, King R. Effect of sex and age on traumatic brain injury: a geographical comparative study. Archives of public health = Archives belges de sante publique. 2017;75.

43. Whelan-Goodinson R, Ponsford J, Johnston L, Grant F. Psychiatric disorders following traumatic brain injury: their nature and frequency. The Journal of head trauma rehabilitation. 2009;24(5).

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44. Lavoie S, Sechrist S, Quach N, Ehsanian R, Duong T, Gotlib IH, et al. Depression in Men and Women One Year Following Traumatic Brain Injury (TBI): A TBI Model Systems Study. Frontiers in psychology. 2017;8.

45. Colantonio A, Harris JE, Ratcliff G, Chase S, Ellis K. Gender differences in self reported long termoutcomesfollowingmoderatetoseveretraumaticbrain injury.BMCneurology. 2010;10.

46. Iverson KM, Hendricks AM, Kimerling R, Krengel M, Meterko M, Stolzmann KL, et al. Psychiatric diagnoses and neurobehavioral symptom severity among OEF/OIF VA patients with deployment-related traumatic brain injury: a gender comparison. Women's health issues : official publication of the Jacobs Institute of Women's Health. 2011;21(4 Suppl).

47. Oyesanya TO, Ward EC. Mental Health in Women With Traumatic Brain Injury: A Systematic Review on Depression and Hope. Health care for women international. 2016;37(1).

48. Farace E,Alves WM.Dowomen fareworse: a metaanalysisofgenderdifferencesin traumatic brain injury outcome. Journal of neurosurgery. 2000;93(4).

49. Verger K, Junqué C, Jurado MA, Tresserras P, Bartumeus F, Nogués P, et al. Age effects on long-term neuropsychological outcome in paediatric traumatic brain injury. Brain injury. 2000;14(6).

50. Babikian T, Asarnow R. Neurocognitive outcomes and recovery after pediatric TBI: metaanalytic review of the literature. Neuropsychology. 2009;23(3).

51. Asemota AO, George BP, Bowman SM, Haider AH, Schneider EB. Causes and trends in traumatic brain injury for United States adolescents. Journal of neurotrauma. 2013;30(2).

52. Galgano M, Toshkezi G, Qiu X, Russell T, Chin L, Zhao LR. Traumatic Brain Injury: Current Treatment Strategies and Future Endeavors. Cell transplantation. 2017;26(7).

53. Carney N, Totten AM, O'Reilly C, Ullman JS, Hawryluk GW, Bell MJ, et al. Guidelines for theManagementof Severe TraumaticBrainInjury, FourthEdition.Neurosurgery.2017;80(1).

54. Stein DM, Feather CB, Napolitano LM. Traumatic Brain Injury Advances. Crit Care Clin. 2017;33(1):1-13.

55. Lippa SM, Brickell TA, Bailie JM, French LM, Kennedy JE, Lange RT. Postconcussion Symptom Reporting After Mild Traumatic Brain Injury in Female Service Members: Impact of Gender, Posttraumatic Stress Disorder, Severity of Injury, and Associated Bodily Injuries. The Journal of head trauma rehabilitation. 2018;33(2).

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Commentary

Reducing harm from the cloud: Internet based cognitive behavioural therapy for opioid use disorder

1University of Toronto, Toronto, Ontario, Canada

2Royal College of Surgeons in Ireland, Dublin, Leinster, Ireland

Keywords: opioid use disorder, cognitive behavioural therapy, virtual

Corresponding authors: bowenma.ma@mail.utoronto.ca, wadeedirfan20@rcsi.com

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Introduction

Overthepasttwodecades,more than 600,000people havediedfrom anopioidoverdosein Canada and the United States (1). The opioid epidemic, also known as the opioid crisis, refers to an everincreasing number of hospitalizations and deaths related to opioid use. This epidemic began in the late 2000s as a result of fraudulent advertising by pharmaceutical companies, inappropriate opioid prescription by physicians, and the introduction of synthetic opioids such as fentanyl (2). While communities and governments have since begun to take action in an effort to curb the effects of this epidemic, an estimated 1.2 million individuals will die as a result of opioid use by 2029 (1). Factors that may have contributed to this grim projection include poor government funding, a lack of resources in rural communities, the social demographic of individuals who are otherwise unable to access current treatments, and a lack of social support which has only been exacerbated by the COVID-19 pandemic (3).

Currently, there are several treatment and harm reduction services available in Canada for people who use drugs (PWUD) to address the growing opioid epidemic which include rehabilitation programs, safe injection sites, mental health support, as well as increased education and awareness. Of these, there are three major pillars of treatment emerging throughout the country: use of naloxone, use of opioid agonist therapies, and the introduction of overdose prevention centres (OPCs) (4).

Naloxone is an opioid antagonist that can be administered intravenously, intramuscularly, subcutaneously, or intranasally to confer a life-saving effect in the event of an opioid overdose. As such, naloxone distribution programs were established throughout the country, allowing PWUD to access the life-saving drug for free at pharmacies, receive take-home kits, while also having access to a healthcare professional (HCP). However, the associated limitations of accessibility, inadequate government funding, and lack of human resources have stalled the upscale of this program. The use of injectable opioid agonist treatment (IOAT) is one of the emerging treatment programsinCanada. Althoughno national program hasbeen established,a pilotprogramin British Columbia that employs the agonist Dilaudid has generated some evidence of reducing withdrawal symptoms (5) OPCswere the first line of treatment established in response to the opioid epidemic. Since its inception, along with security, OPCs also offer addiction counselling, education, and HIV testing (4).

The major issues associated with the services above are accessibility, resource requirements, and political opposition. As such, the ideal efficacy of these programs suffers massively due to the lack of human resources, inability of patients to adhere (due to conditions beyond their control) and difficulty of expansion. A mode of therapy that foregoes the overdependence and excessive use of medication and its associated distribution challenges is cognitive behavioural therapy (CBT).

Cognitive behavioural therapy (CBT), a form of psychotherapy, is a first-line recommendedadjuvant in additionto medicationfor thetreatmentof manysubstanceusedisorders including opioid use disorder (6). Many patients with opioid use disorders suffer from chronic pain

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and psychiatric comorbidities that can lead to relapses during the course of their treatment (7). However, with CBT, patients recovering from addiction and comorbid psychiatric conditions are taught to manage their comorbidities by finding connections between how their thoughts, feelings, and actions can impact their recovery (8). Along with increased relapse prevention and improved coping strategies, CBT also instills destigmatizing awareness within the patient, empowering them to let go of false beliefs and insecurities that may lead to addiction (8).

Despite the many advantages of CBT, its requirement of in-person delivery, long wait times, financial costs, time commitment, stigma, and limited access in rural communities decrease theoverall effectiveness oftheprogram(5). Withthe adventof modern technologyand widespread distribution of smart devices, a novel form of CBT, internet-based cognitive behavioural therapy (iCBT), can help bridge the gap in the treatment of opioid use disorder by addressing such limitations. iCBT is psychotherapy provided through a computer or mobile device and delivered through a digital platform. iCBT can be self-directed or guided by a professionally trained therapist.

Currently, the government of Ontario has partnered with two digital health companies, MindBeacon and Morneau Shepell, to provide free iCBT for both medical residents and healthcare workers in efforts to mitigate the impact of the pandemic on mental health (9). The iCBT programs offered by both companies are similar in that they are self-paced, therapist-guided, condition specific, and require 12 weeks to complete (10, 11). Thus, there is an existing infrastructure upon which further internet-based programs can be delivered.

Several studies speak to the efficacy of iCBT programs. Research conducted by the California Institute of Neuroscience and Psychology demonstrated that iCBT was an effective treatment in the area of depression, with post-questionnaire results showing decreased depressive symptoms and reduced suicidal ideation (12). Moreover, the study also demonstrated a reduction in negative symptoms and seeking behaviour among cannabis users (12). A meta-analysis of RCTs using iCBT for the treatment of depression and anxiety during the Covid-19 pandemic demonstrated a significant decrease in both psychiatric conditions (p<0.0000 and p<0.00001 for depression and anxiety respectively) (13).

This data has also been reproduced within the province of Ontario. Research conducted by Health Quality Ontario showed symptom reduction for moderate major depression (SMD = 0.83, 95% CI 0.59–1.07), generalized anxiety disorder (SMD = 0.84, 95% CI 0.45–1.23) and panic disorder (SMD= 1.15, 95% CI: 0.94 to 1.37) (14). In addition to the medical benefits, patient feedback described the autonomy afforded by iCBT, providing them greater control of their time, location, and pace of therapy (14). Thus, the effect is two-fold: the efficacy of the program itself and its high accessibility that further magnifies such therapeutic effectiveness.

Furthermore, the effect of iCBT has also been applied to substance disorder, demonstrating a reduction in alcohol misuse (15) Specific for iCBT and opioid use disorder, a meta-analysis conducted by Wayah et al. demonstrated decreased relapse rates among patients provided with iCBT along with standard treatment when compared to standard treatment alone, with 91% of patients in the iCBT group showing opioid-negative urine samples compared to 64% in the

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standard treatment group (16). Moreover, a study conducted by the University of Dartmouth further illustrated a decreased odds ratio of patients treated with iCBT having a positive-opioid urine test (OR = .07, 95% CI = .01, .81, p = .03) (17)

Proposal

Given the pre-existing infrastructure of iCBT programs in Ontario along with significant evidence speaking to its efficacy, the potential for upscale and expansion of iCBT in the context of opioid misuse is promising. Our proposal makes full use of two major advantages currently in place: the utility of a pre-existing iCBT platform and the evidence-based efficacy of iCBT programs. Thus, we advocate for the creation of a digital technology grant funded by the government of Canada for corporations to develop an opioid specific iCBT program. As mentioned, iCBT platforms such as Mindbeacon and Morneau Shapell provide a variety of programs that address a series of psychiatric conditions. Mindbeacon specifically, offers services in the context of alcohol misuse (11). As a result of a partnership with Health Ontario, these services are freely accessible to Ontario residents. Yet, there are none in place that specifically target opioid addiction. Given the current health status and growing opioid epidemic in rural populations, the development of an iCBT program specific to opioid addiction is warranted.

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The proposed grant would be specific to corporations with an existing slate of iCBT programs. This intends to facilitate the development of a novel program overseen by organizations with previous experience and infrastructure. However, the grant itself would only be offered to those whose treatment incorporated a set of necessary program objectives, ensuring that the new iCBT

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Figure #1: iCBT Program Objectives (18)

program effectively and specifically addressed the issue of opioid addiction (Figure #1). Based on the works of Dr. Kathleen M. Carrol, a clinical scientist in the Yale Department of psychiatry who made seminal contributions in addiction medicine, our program objectives are well grounded in validated treatment principles in the field of therapy for drug addiction. As demonstrated by previous iCBT studies, the national upscaling of iCBT would have a significant impact on the opioid epidemic while also addressing the barriers in existing services today. Given the internetbased delivery, iCBT confers increased accessibility and by-passes geographic limitations that impede service to rural communities. Moreover, the internet-based model has also shown to increase adherence among patients as the service can be accessed in the comfort of one’s home (4). But perhaps the greatest advantage of the iCBT program comes from anonymity. As mentioned, stigma and discrimination are rampant when associated with PWUD, which discourages health-seeking behaviour. The anonymous nature of iCBT allows patients to avoid this stigma and allow them to access the help they need (4).

In addition to therapeutic effectiveness, there would long term financial benefits associated with the grant; the prioritization and increased dissemination of iCBT is associated with decreased cost per patient. A study that modeled the implementation of iCBT based on established cost, waittimes, and quality-adjusted-life years in Germany saw a cost saving of €2536 per patient compared to compared with face-to-face CBT (FCBT) in 3 years' time (19). Moreover, in their probabilistic sensitivity analysis, they suggest that iCBT is highly likely to be more effective (91.5%), less costly (76%), and the dominant strategy (69.7%) compared to FCBT (19)

Conclusion

With the ever-growing opioid epidemic, the need for new and innovative solutions is increasing. The current major modes of opioid addiction therapy such as naloxone clinics, IOAT, and OPCs have proven to be effective. However, they suffer from significant barriers; limited accessibility to rural communities, inadequate government funding, lack of human resources and restrictive political policies impede the effectiveness of established programs.

Traditional in-person CBT has been well researched since its inception and is considered the first-line treatment for many medical conditions including opioid addiction. While nascent in comparison, iCBT has the potential to deliver unparalleled accessibility for patients and cut costs for a burdened healthcare system. With evidence-based efficacy and pre-existing basal infrastructure, there is significant foundation to upscale iCBT to address the opioid crisis.

We recognize that iCBT in the setting of opioid addiction is a novel approach. As such, the future of implementation requires an interdisciplinary approach and analysis to ensure the establishment of an effective treatment program. Government officials, social workers, healthcare professionals, communication technology professionals and science academia will all be required to ensure the validation and delivery of an effective opioid addiction treatment.

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References

1. Opioid overdose crisis: time for a radical rethink. The Lancet Public Health. 2022;7(3):e195.

2. Howlett K. Canada's Opioid Crisis Canada: The Canadian Encyclopedia; [updated 17 September 2020; cited 30 July 2022]. Available from: https://www.thecanadianencyclopedia.ca/en/article/canadas-opioid-crisis.

3. Government of Canada. Opioids Canada: Government of Canada; [updated 5 July 2022; cited 30 July 2022]. Available from: https://www.canada.ca/en/healthcanada/services/opioids.html.

4. Strike C, Watson TM. Losing the uphill battle? Emergent harm reduction interventions and barriers during the opioid overdose crisis in Canada. International Journal of Drug Policy. 2019;1(71):178-182.

5. Mohr DC, Hart SL, Howard I, Julian L, Vella L, Catledge C, Feldman MD. Barriers to psychotherapy among depressed and nondepressed primary care patients Annals of Behavioral Medicine. 2006;32(3):254-8.

6. McHugh RK, Hearon BA, Otto MW. Cognitive behavioral therapy for substance use disorders. Psychiatric Clinics. 2010 Sep 1;33(3):511-25.

7. Wall D. Opiod use disorder: Fact sheet: ABCT Association for Behavioral and Cognitive therapies; [cited 30 July 2022]. Available from: https://www.abct.org/fact-sheets/opiod-usedisorder/#:~:text=Because%20chronic%20pai n%20is%20highly,people%20with%20opioid%20use%20disorder.

8. Hartney E. Cognitive Behavioral Therapy (CBT) for Substance Abuse and Addiction Verywell Mind; [updated 2021; cited 30 July 2022]. Available from: https://www.verywellmind.com/cognitive-behavioral-therapy-for-addiction-21953.

9. Office of the Premier. Ontario Expands Virtual Mental Health Services During COVID-19 Government of Ontario; [cited 30 July 2022]. Available from: https://news.ontario.ca/en/release/56847/ontario-expands-virtual-mental-health-services-d uring-covid-19.

10. Our Programs [Internet]. AbilitiCBT. Lifeworks; [cited 2022Jul30]. Available from: https://myicbt.com/en-CA/programs

11. Mindbeacon. Guided CBT Programs: Mindbeacon Software Inc. [cited 30 July 2022]. Available from: https://www.mindbeacon.com/guided-cbt-programs.

12. Kumar V, Sattar Y, Bseiso A, Khan S, Rutkofsky IH. The effectiveness of internet-based cognitive behavioral therapy in treatment of psychiatric disorders. Cureus. 2017:29;9(8).

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13. Komariah M, Amirah S, Faisal EG, Prayogo SA, Maulana S, Platini H, Suryani S, Yosep I, Arifin H. Efficacy of Internet-Based Cognitive Behavioral Therapy for Depression and Anxiety among Global Population during the COVID-19 Pandemic: A Systematic Review and Meta-Analysis of a Randomized Controlled Trial Study. Healthcare. 2022;10(7):1224.

14. Internet-delivered cognitive behavioural therapy for major depression and anxiety disorders: a health technology assessment. Ont Health Technol Assess Ser [Internet]. Health Quality Ontario. 2019 Feb [cited 2022Mar6];19(6):1– 199. Available from: http://www.hqontario.ca/evidence-to-improve-care/journal-ontario-healthtechnologyassessment-series

15. Hadjistavropoulos HD, Mehta S, Wilhelms A, Keough MT, Sundström C. A systematic review of internet-delivered cognitive behavior therapy for alcohol misuse: study characteristics, program content and outcomes. Cognitive Behaviour Therapy. 2020;49(4):327-46.

16. Wayab SB, Waziri PM, Onyebuchi CM, Yahaya G, Chindo BA. Phychosocically-Assisted Pharmacological Treatment of Opioid Dependent Adults: A Systematic Review. Ibom Medical Journal. 2022;15(3):197-208.

17. Saunders EC, McGovern MP, Lambert-Harris C, Meier A, McLeman B, Xie H. The Impact of Addiction Medications on Treatment Outcomes for Persons with Co-Occurring PTSD and Opioid Use Disorders. The American Journal on Addictions. 2015;24(8):722-731.

18. Carroll KM. Therapy Manuals for Drug Addiction. Rockville, MD: U.S. Dept. of Health and Human Services, National Institute on Drug Abuse; 1998.

19. Baumann M, Stargardt T, Frey S. Cost–utility of internet-based cognitive behavioral therapy in unipolar depression: A Markov model Simulation. Applied Health Economics and Health Policy. 2020;18(4):567-78.

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Original Research Article

Weight before you judge: Investigating prevalence, manifestations and changes in weight bias attitudes throughout medical education

1McMaster University, Hamilton, Ontario, Canada

2University of Ottawa, Ottawa, Ontario, Canada

3School of Public Health, University of Alberta, Edmonton, Alberta, Canada

4Canadian Obesity Network, University of Alberta, Edmonton, Alberta, Canada

5Wharton Medical Clinic, Burlington, Ontario, Canada

6Toronto East General Hospital, Toronto, Ontario, Canada

7Hamilton Health Sciences, Hamilton, Ontario, Canada

8University of Alberta, Edmonton, Alberta, Canada

9Memorial University, St. John’s, Newfoundland and Labrador, Canada

Abstract

Purpose: Individuals with obesity are common targets of discrimination due to pervasive weight bias. Of concern is the prevalence of weight bias among healthcare workers, including medical students who represent the future of medical practitioners and will be directly involved in the care of patients living with obesity. The purpose of this review is to outline studies that investigated explicit, implicit, and internalized weight bias attitudes among medical students, changes in weight bias over the span of the medical program, and manifestations of weight bias during clinical encounters.

Methods:  A keyword search was conducted in PubMed, EMBASE, and PsycInfo databases based on following themes: (i) implicit weight bias/stigma, (ii) explicit weight bias/stigma, (iii) weight bias internalization, and (iv) medical students. A total of 26 articles were selected and reviewed.

Results:  Explicit and implicit weight bias is a global issue impacting medical students. There is evidence to suggest that explicit weight bias increases while implicit weight bias decreases throughout the duration of medical school. Data on internalized weight bias among medical students is limited, with only one study suggesting that the perceived stigma that medical students with larger bodies experienced may directly contribute to their negative weight bias attitudes. Moreover, weight bias attitudes among medical students manifests itself in clinical encounters with patients who are overweight or obesity.

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Meena Saad MD1 , Marina Saad MD2 , Abanoub Aziz Rizk MD2 , Ximena Ramos Salas PhD3,4 , Sean Wharton MD PharmD FRCPC5-7 , Arya M. Sharma MD DSc(hon) FRCPC8 , Laurie Twells Msc PhD9

Conclusion:  Information from this review highlights the significance of weight bias among medical students and can be used by program directors to gain insight into the prevalence and complexity of weight bias.  This is then applied to advocate for the incorporation of appropriate anti-weight bias interventions in their undergraduate medical program.

Keywords: Weight bias, implicit, explicit, medical student, obesity

Corresponding author: meena.saad@medportal.ca

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Introduction

Obesity is a chronic disease, defined as abnormal or excess body fat that negatively impairs health (1, 2). Epidemiological studies measure obesity using the Body Mass Index (BMI) (weight divided by height in meters squared). The prevalence of obesity in Canada (as measured by BMI) has nearly tripled between 1985 to 2011 (3). In 2018, it was estimated that 26.8% of Canadians have a BMI over 30 kg/m2 which may indicate that they have obesity (4).

Individuals living in a large body or with obesity are common targets of prejudice, stigma, and discrimination due to pervasive weight bias (5). Weight bias can be categorized as explicit, implicit, or internalized (5, 6, 7). Explicit and implicit weight bias refer to conscious and unconscious negative attitudes towards individuals with large bodies, respectively. Alternatively, internalized weight bias refers to the negative attitudes that individuals hold towards themselves due to their weight. Explicit and internalized bias are quantified using a series of validated selfreport measures while implicit bias is traditionally measured using the implicit association test (IAT) (8, 9, 10, 11).

Weight bias is common in society and manifests in diverse settings and across the lifespan (12, 13, 14, 15) Indeed, people with large bodies or living with obesity are often labeled as lazy, less intelligent, unmotivated, and lacking self-control (16, 17, 18) Weight bias also results in stigmatization and discrimination which can cause social and economic inequities and may contribute to negative physical and mental health outcomes (19, 20, 21, 22, 23) Despite the recognition of obesity as complex chronic disease as well as medical, scientific and education efforts to reduce weight bias, people with obesity continue to be stigmatized. In one study, researchers analyzed implicit and explicit attitudes measured continuously over 13 years. They compared attitudes for sexual orientation, race, skin tone, age, disability, and body weight. Most of these measures showed a change towards neutrality over time. However, for body weight implicit attitudeshavemovedaway from neutrality.So,while implicitnegative attitudes have been reduced for all these other areas, weight biased attitudes have increased (24). The prevalence of weight bias in healthcare settings is concerning. Specifically, medical doctors are a cohort known to hold negative attitudes towards individuals with obesity (25, 26, 27, 28). A study in the United States with a random sample of over 600 physicians, more than half of primary care physicians viewed patients with obesity as awkward, unattractive, ugly, and noncompliant (29). Such negative attitudes have been shown to impact the quality and accessibility of health care by patients with obesity (30, 31, 32, 33). Research indicates that doctors that have weight bias spend less time with patient affected by obesity and conduct less interventions including screening for other diseases such as cancer (32). These stigmatizing practices can have serious consequences on the health and wellbeing of patients living with obesity (34). Delayed or lack of diagnosis of other diseases can result in pre-mature mortality. Due to the serious implications of weight bias in the healthcare system, Obesity Canada developed evidence-based recommendations to address weight bias in the 2020 clinical practice guideline for the management of obesity in adults (35) In 2019, the Chief Medical Health Officer for Canada called on all Canadians to end stigma in our society (36) Internationally, there is a recognition

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that weight bias and stigma is affecting the right to health for individuals living with obesity. Moreover, scientific and advocacy organizations developed an international consensus statement to end obesity stigma in 2020 (37).

Unfortunately, weight bias also extends to students in healthcare professional programs and without targeted interventions, they may continue endorsing negative attitudes towards obesity when they begin their clinical practice (38, 39, 40). Medical students are a particularly important population in which to investigate and address weight bias as they are in the early stages of being socialized to the profession, represent the future of medical practitioners, and will be directly involved in the care of people living with obesity or those living in large bodies.

The purpose of this review is to outline studies that investigated explicit, implicit, and internalized weight bias attitudes among medical students, changes in weight bias over the span of the medical education, and manifestations of weight bias during clinical encounters. Information from this review can be used by medical education directors and curriculum developers to gain insight into the prevalence, complexity, and predictors of weight bias among medical students and advocate for the incorporation of appropriate weight bias interventions to their undergraduate medical program.

Methods

This narrative review was conducted in accordance to the guidelines outlined in the Cochrane Handbook for Systematic Reviews of Interventions (41). A keyword search, with the expert guidance of a librarian, was conducted in PubMed, EMBASE, and PsycInfo databases based on following themes: (i) implicit weight bias/stigma, (ii) explicit weight bias/stigma, (iii) weight bias internalization, and (iv) medical students (Table 1).

The predetermined inclusion criteria for this review included: original research articles in the English language that investigated explicit, implicit, and/or internalized weight bias among undergraduate medical students in any year of their medical program. Exclusion criteria included:

(i) commentaries, editorials, letters, literature reviews, conference abstracts, theses and gray literature, (ii) weight bias in non-medical student populations, (iii) studies that examined educational interventions that target weight bias but did not directly measure or investigate weight bias, and (iv) studies that only investigated weight bias post-intervention. Our search yielded 756 abstracts. After the removal of 103 duplicates, two authors independently screened the remaining 653 titles/abstracts. When required, consensus was reached through discussion. A full text review of the 41 articles that met the inclusion criteria for the title/abstract screening was conducted by the same authors. A total of 26 articles were selected for the purpose of this literature review (See Figure 1).

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Keyword and Mesh Strategy

PubMed (("Bias"[Mesh] OR "Social Stigma"[Mesh] OR "Prejudice"[Mesh] OR "Social Discrimination"[Mesh] OR "Attitude"[Mesh] OR Bias OR Stigma* OR Prejudice OR Discriminat* OR Attitude* OR Judge OR "Anti fat" OR "Anti Obese" OR "Fat phobia" OR Label OR Shame OR Shaming OR Intolerance OR Perception OR "Social acceptance" OR "Social approval" OR Sterotyp*) AND ("Body Weight"[Mesh] OR "Body Weight" OR Weight OR "Body size" OR "Body shape" OR Obesity OR Obese OR Overweight OR Underweight OR Fat OR Thin OR Thinness OR Skinny OR "Body Mass Index") AND ("Students, Medical"[Mesh] OR "Medical student" OR "Medical students" AND "Education, Medical"[Mesh] OR "Lecture" [Publication Type] OR "Program Development"[Mesh] OR "Surveys and Questionnaires/education”[Mesh] OR OSCE))

EMBASE ('social stigma'/exp OR 'prejudice'/exp OR 'social discrimination'/exp OR 'attitude'/exp OR 'social stigma' OR prejudice OR discriminat* OR attitude* OR judge OR 'anti fat' OR 'anti obese' OR 'fat phobia' OR label OR shame OR shaming OR intolerance OR perception OR 'social acceptance' OR 'social approval' OR sterotyp*) AND ('body weight'/exp OR 'body weight' OR weight OR 'body size' OR 'body shape' OR obesity OR obese OR overweight OR underweight OR fat OR thin OR thinness OR skinny OR 'body mass index') AND ('medical student'/exp OR 'medical student' OR 'medical students') AND ('medical education' OR 'osce' OR 'lecture based learning' OR 'teaching' OR 'questionnaire')

PsychInfo ((DE "Stigma" OR DE "Social Discrimination" OR DE "Attitudes" OR DE "Prejudice" OR stigma* OR prejudice OR Discriminat* OR Attitude* OR Judge* OR "Anti fat" OR "Anti obese" OR "Fat phobia" OR Label* OR Shame OR Shaming OR Intolerance OR perception* OR Bias OR "social acceptance" OR "Social approval" OR Sterotyp*) AND (DE "Body Size" OR "Body Weight" OR Weight OR "Body size" OR "Body shape" OR Obesity OR Obese OR Overweight OR

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Table 1. Review search strategy utilizing PUBMED, EMBASE and PsychInfo

Underweight OR Fat OR Thin OR Thinness OR Skinny OR "Body Mass Index") AND (DE "Medical Students" OR "Medical student" OR "Medical student" AND (medical education OR Lecture OR OSCE))

Results

Explicit weight bias

A total of 16 studies, ranging from 1985 to 2019, investigated the presence of explicit weight bias in medical students. The results generally indicated that medical students exhibited explicit weight bias throughout all stages of their undergraduate medical education (42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56). Indeed, results from a national study that investigated 4,732 medical students across 49 medical schools in the United States indicated that 67% of first year medical students had explicit weight bias and 39% of students exhibited a strong anti-fat bias (51).

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Figure 1. PRISMA Flowchart

Moreover,60%and16%ofmedicalstudentsagreed withthephrases: “somepeoplearefatbecause they have no will power” and “I don’t like fat people very much,” respectively. Medical student explicit weight bias was much more pronounced relative to biases towards race, homosexuality, and socioeconomic status (51). Medical students also had greater explicit weight bias in comparison to other health-care students and professionals (45, 55). One study found that medical students exhibited a high level of empathy, despite their pronounced explicit weight biases scores (50) A study that investigated explicit weight bias utilizing a novel self-report questionnaire that is specifically designed for medical students found that medical students had a slightly positive attitude towards individuals with obesity (46) Nevertheless, the results were correlated with the scoresfromthetwoothervalidated explicitweightbiasmeasureswhichtraditionallydemonstrated explicit weight bias in this student cohort. Overall, explicit weight bias appears to be a universal issue that is exhibited by medical students in many countries, including: the United States, United Kingdom, Australia, Germany, and Mexico (42, 45, 49, 51, 52)

Implicit Weight Bias

Medical students exhibited implicit weight bias attitudes in all years of their medical education (47, 50, 51, 52, 57, 58, 59). A national study conducted in the United States indicated that majority of first year medical students had a moderate-severe implicit weight bias.52 Similarly, another study concluded that 39% of third year medical students in the United States had implicit weight bias (47). Implicit weight bias was also present in Australian medical students, indicating that similar to explicit weight bias, implicit weight bias is a global issue that is not limited to medical students in North America (52). One study investigated medical student implicit weight bias using a novel quantitative assessment tool known as the Implicit Relational Assessment Procedure (IRAP) (57).The IRAP was proposed to allow for a more in-depth analysis and comprehensive conclusions of implicit bias relative to the IAT. Indeed, while the IAT is limited to pro-thin/anti-fat, pro-fat/anti-thin, or neutral bias conclusions when assessing weight bias, results from the IRAP can suggest that individuals are also pro-thin/pro-fat or anti-thin/antifat. Results from the IRAP study indicated that medical students have both pro-thin and profat bias but are more likely to have the former relative to the latter.

Weight Bias Internalization

Only one study investigating weight bias internalization among medical students was identified (60). This national study conducted in the United States demonstrated that first year medical studentswithlargebodyhabituswere more likelytoreportexperiencingstigmarelativeto students who had underweight/normal weight and they exhibited significant explicit and implicit weight bias attitudes (60).Internalized weight bias in the medical student cohort resulted in worse overall

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health and self-esteem outcomes relative to students with underweight/normal weight. Although this study did not quantify internalized weight bias using traditional psychometric tools for this subtype of bias, the results were indicative that the perceived stigma that students with larger bodies experienced may have been directly contributed to their negative weight bias attitudes.

Changes in Weight Bias Throughout the Medical Program

Changes in both explicit and implicit weight biases were observed as medical students progressed through their medical education. Indeed, a longitudinal national study in the United States demonstrated that explicit weight bias increased throughout the four years of medical school (61) Thisfinding issupported byanotherstudy which found that fourth year medicalstudentsexhibited significantly greater explicit weight bias relative to second year students (46) Alternatively, implicit weight bias was shown to decrease as students progressed through their medical education (57, 61). Reductions in both explicit and implicit weight bias were associated with positive interactions with patients living with obesity. Increases in explicit and implicit weight bias were associated with observations of discriminatory behaviour from faculty towards patients living with obesity (61). Moreover, the belief that obesity was the consequence of genetic and biological factors negatively correlated with weight bias, suggesting the importance of shifting from solely attributing obesity to controllable factors that contribute to blaming and shaming the individual with obesity (56).

Weight Bias Manifestation

In addition to identifying weight bias among medical students, several studies attempted to investigate themanifestation ofsuchattitudesduring clinical encounters.Overall,medicalstudents exhibited negative attitudes towards patients who had overweight/obesity during clinical encounters but there was no evidence to indicate that clinical recommendations were influenced by the patient’s weight status (62, 63, 64, 65) In one study, third- and fourth-year medical students interviewed either a virtual patient with obesity or a patient without obesity, who presented with two-weight related complaints and one regular complaint (64). Compared to the control group, medical students who interviewed the patient with obesity engaged in less eye contact and were more likely to believe that the patient was less healthy, less likely to adhere to advice, and was responsible for their weight-related complaints. Another study also utilized virtual reality demonstrated that both Caucasian and non-Caucasian first year medical students perceived white female avatars with obesity to be more sloppy, non-compliant, lazy, unattractive, and ugly relative to other avatars in the study (65). Non-Caucasian medical students had the most negative attitude towards the white avatar woman with obesity while Caucasian students had equal negative attitudes towards both black and white avatars with obesity.

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Discussion

Weight bias is a serious issue that may persist into future generations of healthcare professionals. This is the first review comparing explicit, implicit, and internalized weight bias in relation to the transition throughout the four years of undergraduate medical education. This unique perspective seeks to inspire further work as to better tailor our interventions to the level of student training. Thisreviewoutlinedstudies that investigated explicit, implicit, andinternalizedweight biasamong medical students, changes in weight bias as students progressed throughout medical school, and clinical manifestations of such attitudes in their interactions with patients living with obesity or in large bodies.

Both explicit and implicit weight bias attitudes were demonstrated to be significant in this unique student cohort. Although the majority of studies were conducted in the United States, there is significant evidence to suggest that this is a global issue that requires a unified call for action (37). These findings were consistent with results from other studies investigating weight bias among healthcare students (38, 39, 40). An important finding of this review is that explicit weight bias increases while implicit weight bias decreases throughout medical school (46, 57, 61). Such results are contrary to data from the general public, which indicate that explicit weight bias attitudes have decreased and implicit weight bias attitudes continue to increase (66).Alternatively, the increase in explicit weight bias could be due to the continuous exposure of students to stigmatizing behaviour and derogatory comments from physicians and mentors towards patients with obesity (39, 61, 66, 67). Consequently, exposure to such negative attitudes may normalize and exacerbate explicit weight bias. Explicit weight biases in medical students can also be influenced by the challenges and frustration associated with the lack of training on obesity assessment, diagnosis, and treatment that medical students face (66). Most medical training programs do not offer obesity or weight bias education (68)

Unfortunately, to our knowledge, no weight bias intervention to date has demonstrated long-term efficacy among medical students. Based on the findings outlined in this review,it isrecommendedthatmedicalprogramsintroduceeducationalinterventionsthatintegrate obesity related clinical skills training during the early stages of the medical program. This will allow students to develop the skills necessary to examine and manage obesity-related presentations in a safe learning environment. Moreover, interventions are encouraged to educate medical learners about the pertinent influence of genes and biology in determining an individual’s body weight, thus shifting from the view that obesity is the consequence of moral failing and lack of willpower (55, 69). Another recommendation is to offer faculty/mentors “train the trainer” programs focused on obesity, weight bias and obesity stigma.

There is evidence demonstrating that if patients perceive weight bias and stigma from their physicians, ey will avoid future contacts with that practitioner, they will have less trust in their doctor, and will engage in doctor shopping (32). This can have major implications for the health and wellbeing of patients. In addition to including self-reflection training programs as part of existingmedicaleducationprograms’Equity,Diversity,andInclusion

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(EDI)work,werecommend

creating weight bias and sensitivity programs to improve communications skills among medical students. Forexample,person-first language isthe standardforrespectfully addressingindividuals with chronic disease. If health care professionals are interacting with individuals who have been diagnosed with obesity, person-first-language is recommended as it allows both medical students andphysiciansto consciously(andsubconsciously) separatethechronic illnessfromtheindividual and thus avoid labelling a person based on their illness. However, it is also important to educate medical students that not all individuals living in large bodies have obesity. Obesity diagnosis requires a full medical exam to determine if a person’s excess or abnormal adiposity is impairing their health. Students should distinguish between obesity and body size and not make assumptions about a person’s health solely based on their body size and always ask their patients for their preferences in terms of language use and always respect a patient’s personal identity.

In addition to weight bias interventions, future studies are encouraged to develop better psychometric tests that accurately investigate weight bias attitudes and beliefs among medical students, particularly explicit bias. Indeed, most explicit weight bias measures that were used to assess medical student weight bias appear to have outdated terminology that does not employ person-first language and have actually been found to conflate bias in certain circumstances (8, 70). The Nutrition, Exercise, and Weight Management Attitudes Scale is a promising new tool for investigating explicit weight bias among medical students due to the test’s emphasis on clinical topics such as: weight management, counselling, and the weight bias attitudes during clinical settings (46). Despite demonstrating validity and reliability, to our knowledge, it has not been used in studies that have investigate medical student explicit weight bias.

Finally, data on internalized weight bias among medical students was very limited. Given the potential impact of internalized weight bias on influencing the attitude and behaviour of healthcare professionals towards individuals with obesity, future studies are needed to investigate internalized weight bias in medical students and to explore variables that may predict and decrease this specific form of weight bias.

Limitations

Our literature review had a drawback in that the search parameters used might have resulted in the exclusion of certain articles that could have been valuable to our analysis; for instance, articles written in languages other than English that provided valuable insights may have been left out. Furthermore, several of the suggested measures used to assess weight bias were based on the professional judgment of experts rather than empirical data. To illustrate, only a few student surveys were conducted to measure the effectiveness or drawbacks of the interventions implemented, from the standpoint of students. Moreover, as previously alluded to, most of the studies in this review were conducted in the United States which could impact the generalizability of the data. There is, however, evidence to suggest that weight bias is pervasive among medical studentsacross theglobe andamongotherhealth-care students(37, 38,39, 40).Finally,thisreview does include studies spanning several decades, ranging from 1985-2019, where societal norms and

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the overall culture within medicine is highly variable. Indeed, while in earlier years, weight bias was not considered a major hindrance to patient care, the progressive shift towards a more holistic approach, thus, weight bias, along with other biases in healthcare became known as a contributor to the overall health of the patient.

Conclusion

Explicit, implicit, and internalized weight bias play a significant role in the mindset and actions of medical students, who will soon become healthcare providers. This review aimed to shed light on the current prevalence of weight bias among medical students and demonstrate how this can negatively impact the physician-patient collaborations on which the entire healthcare system stands. To our knowledge, this is the first review paper to consolidate explicit, implicit, and internalized weight bias attitudes among medical students on a global scale. In an era where healthcare systems are making commitments to improve equity, diversity and inclusion, medical schools have the opportunity to examine how they can address all forms of systemic bias, stigma, and discrimination faced by patient communities, including people living in large bodies or living with obesity.

Acknowledgements

None.

Funding/ Support

None.

Disclosures

None.

Ethical Approval

None.

Disclaimers

The manuscript has not been previously published and is not under consideration in the same or substantially similar form in any other journal. All those listed as authors are qualified for authorship and order of authorship has been agreed upon by all members of the team.

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Commentary

Cervical Cancer Screening in Transgender Men and Non-Binary People with a Cervix

Abstract

Mortality from cervical cancer is projected to decline over the next several years; however, this estimate relies on the inclusion of all eligible individuals in screening processes. This requires a robust understanding of barriers to routine screening, especially in at-risk populations such as transgender men and those who identify across a trans-masculine spectrum. Barriers include miseducation surrounding screening protocols, distrust in the healthcare system and histological inadequacy of samples obtained. These barriers can be addressed through proper education of both practitioner and patient, appropriate signage and outreach, and adjustments to clinical practices to meet evolving guidelines.

Keywords: cervical cancer, transgender health

Corresponding author: tessa.anzai@medportal.ca

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Introduction

In the era of modern medicine, it can be tempting to place a healthy amount of reliance on preventative health protocols and regimes, and there have certainly been drastic benefits seen from implementation of routine screening and vaccination programs. Cervical cancer is one such example of this, and mortality from cervical cancer is projected to continue declining over the next several years (1). Still, this hardly equates to the diagnosis being eliminated. This projected decrease relies on both continued HPV vaccination programs and participation in screening practices by all eligible individuals and when the more minute details of this plan are examined, limitations become apparent. One of the largest gaps is the inclusion of transgender men (TM) and non-binary individuals with a cervix in these programs. It is becoming more broadly recognized that cervical cancer screening should be conducted in everyone with a cervix regardless of gender identity and while Ontario Cancer screening guidelines have changed their verbiage to reflect this, practical data shows that this is not implemented equally (1,2). This commentary aims to highlight the importance of cervical cancer screening in all individuals with a cervix, covers details that are glossed over in medical school curriculum (3), and primes readers to future developments in the field.

Cervical Cancer Screening in Trans Males

Cervical cancer screening practices should be applied uniformly to all individuals with a cervix, which includes TM with a cervix. It has been previously reported that approximately 21% of TM have undergone gender-confirming total hysterectomies, thus 79% of patients require regular cervical cancer screening. These screening practices should be applied to TM patients regardless of history of penetrative vaginal intercourse (1). This is in part since HPV vaccination rates are lowest in TM, with a prevalence of only 20% (4). Overall, TM patients are up to 18% less likely to receive routine cervical cancer screening in comparison to cis females. This can be due to lack of education on the part of both patient and practitioner, discomfort or distrust in the healthcare system, or exclusion from systemic screening programs that use patients’ health records if they’ve legally changed their sex to male (5).

The rate of inadequate samples is 8 times greater than for cis females (6). This is attributed toscantcellularityandvaginal atrophyfromuseof androgentherapy. Thetemporaryuseofvaginal estrogen 1-2 months before the exam can help prevent this complication; however, the feasibility of patient adherence to this approach is low. Following an inadequate result, the average length of time before a repeat sample is taken has been found to be significantly longer for TM when compared to cis females, further increasing the risk for a true abnormal cytology finding to go undetected for a longer period (6).

Inclusive Healthcare Strategies

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There are several steps that can be taken by healthcare providers to combat this issue. Care should be taken to create a structurally affirming clinic environment. This includes the entire duration of the patient experience, from front-of-house signage, to the procedure itself, to follow-up afterwards. A safer and more supportive clinic space can be developed by encouraging cultural competency training for all staff, ensuring that adequate pronouns and preferred names are used, the availability of gender-neutral bathrooms, and avoidance of cisgender assumptions (for example, on intake forms, and for clinic names such as “Women’s Health” clinics). Practitioners should take care to minimize patient distress during sensitive exams. Important considerations include the use of neutral language (Table 1) and trauma-informed care and examinations, as well as the use of non-interfering lubricant and a smaller-sized speculum as needed (6). It is important for practitioners to recognize that pelvic exams hold the potential for re-traumatization of TM patients in addition to the physical discomfort of the exam. This can come from heightened emotions related to gender dysphoria associated with the exam itself, the language used by the healthcare professional, or the menstrual-like spotting that is common after a cervical cancer screening (6).

Table 1. Examples of non-sexualized language for use during pelvic examinations

Gendered/Negative Connotation

Neutral/positive connotation

Vulva External pelvic area

Outer genitalia

Labia Outer folds

Vagina

Uterus, ovaries

Pap smear

Period/Menstruation

Stirrups

Genital opening, frontal pelvic opening, internal canal

Internal organs

Cancer screening

Cancer, HPV-related cancer

Bleeding

Footrests

“Scoot down until your bottom touches my hand” Ask patient to move to the end of the table

“Open your legs”

“Blades of the speculum”

“I’m going to insert the speculum”

“You’re going to feel a little poke”

Adapted from Potter J. (7, 8)

HPV DNA Testing

“Let your legs drop to either side”

“Point your knees to the wall”

“Bills of the speculum”

“Opening the speculum”

“You may feel some pressure”

Practitioners and medical trainees alike should be aware of alternate options to PAP smear screening, and that provincial guidelines around cervical cancer screening are quickly evolving. Emerging evidence reveals that HPV DNA testing is more sensitive than traditional testing with pap smears (9). It can be self-collected and thus less invasive, providing a more comfortable

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experience for some patients. While self-swab HPV tests are not yet approved in most provinces, this is expected to change in the coming years. Ontario Cervical Cancer guidelines already acknowledge that this change is coming and that recommendations will be shifting. There is not yet a timeline in place for this; however, and thus remains an area of future advancement. Current guidelines do not specifically include transgender patients as a patient population where testing beginning at the age of 21 is indicated; instead, inclusion criteria in accordance to the most recent provincial guidelines should be applied to these patients (2).

Conclusion

Trans health remains an overlooked aspect of the medical school curriculum, and the changes that are made for current students will take several years to be fully implemented. It is essential for practitioners to remain updated on current guidelines and barriers to implementation to adequately treat their patients. TM patients are less likely to be up to date on cervical cancer screening and barriers to this are multifactorial, including inadequate histology of samples, avoidance on part of the patient, their experience interacting with physicians, and education of both parties. Strategies to address these barriers include prioritizing affirming clinic experiences for patients and ensuring practices reflect updated guidelines.

References

1. Beswick A, Corkum M, D’Souza D. Locally advanced cervical cancer in a transgender man. CMAJ. 2019 Jan 21;191(3):E76-8.

2. Murphy J, Kennedy E, Dunn S, Fung Kee Fung M, Gzik D, McLachlin CM, et al. Ontario Cervical Cancer Screening Program (OCSP) Screening Recommendations Summary [Internet]. Toronto (ON): Cancer Care Ontario; 2011 Oct 5 [cited 2022 Jan 6]. Available from https://www.cancercareontario.ca/en/guidelines-advice/types-of-cancer/2156

3. Nolan IT, Blasdel G, Dubin SN, Goetz TG, Greene RE, Morrison SD. Current state of transgender medical education in the United States and Canada: Update to a scoping review. Journal of Medical Education and Curricular Development. 2020 Jun;7:2382120520934813.

4. Weyers S, Garland SM, Cruickshank M, Kyrgiou M, Arbyn M. Cervical cancer prevention in transgender men: a review. BJOG: An International Journal of Obstetrics & Gynaecology. 2021 Apr;128(5):822-6.

5. Kiran T, Davie S, Singh D, Hranilovic S, Pinto AD, Abramovich A, Lofters A. Cancer screening rates among transgender adults: cross-sectional analysis of primary care data. Canadian Family Physician. 2019 Jan 1;65(1):e30-7

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6. Peitzmeier SM, Reisner SL, Harigopal P, Potter J. Female-to-male patients have high prevalence of unsatisfactory Paps compared to non-transgender females: implications for cervical cancer screening. Journal of general internal medicine. 2014 May 1;29(5):778-84.

7. PotterJ,PeitzmeierSM,BernsteinI, Reisner SL,AlizagaNM,AgénorM,Pardee DJ.Cervical cancer screening for patients on the female-to-male spectrum: a narrative review and guide for clinicians. Journal of general internal medicine. 2015 Dec;30(12):1857-64. Table 3, Gender-neutral language for use during pelvic examinations; p. 1860.

8. PotterJ,PeitzmeierSM,BernsteinI, Reisner SL,AlizagaNM,AgénorM,Pardee DJ.Cervical cancer screening for patients on the female-to-male spectrum: a narrative review and guide for clinicians. Journal of general internal medicine. 2015 Dec;30(12):1857-64. Table 4, Examples of non-violent, non-sexualized language for use during pelvic examinations; p. 1861.

9. Reisner SL, Deutsch MB, Peitzmeier SM, White Hughto JM, Cavanaugh TP, Pardee DJ, McLean SA, Panther LA, Gelman M, Mimiaga MJ, Potter JE. Test performance and acceptability of self-versus provider-collected swabs for high-risk HPV DNA testing in female-to-male trans masculine patients. PLoS One. 2018 Mar 14;13(3):e0190172.

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