Caring for Sexual and Gender Minority Patients: What Factors Explain Self- Reported Competence Among Healthcare Professional Students?

December 2021 Vol 12, No 12


Original Research
Mandi Pratt-Chapman, MA, PhD, HON-OPN-CG
Associate Center Director,
Patient-Centered Initiatives & Health Equity,
GW Cancer Center
Washington, DC
Jennifer Potter, MD
Harvard Medical School, Department of General Medicine, Boston, MA
Beth Israel Deaconess Medical Center, Women’s Health Center, Boston, MA
The Fenway Institute, Boston, MA

Background: Lesbian, gay, bisexual, transgender, queer, and intersex people comprise approximately 5% of the US population, yet healthcare professional student education on sexual and gender minority (SGM) health is sparse.

Objective: This study explored the degree to which sociodemographic factors and student affiliation with SGM people explained self-reported competence of healthcare professional students in caring for SGM patients.

Methods: A sample of healthcare professional students attending one urban university (N = 48) were selected from the control group (n = 134) of another study. Multiple linear regression was used to test value of an 8-variable exploratory (Full Model) for each of 5 criterion variables. Independent variables that explained a meaningful amount (≥.15) of total variance were retained in Reduced Models for parsimony. Criterion variables were Basic Knowledge, Attitudinal Awareness, and Clinical Preparedness (subscales of the Lesbian, Gay, Bisexual, Transgender Development of Clinical Skills Scale), and Beliefs and Behaviors (subscales of the Gay Affirming Practice Scale).

Results: Liberal political affiliation, less religiosity, and affiliation with SGM people explained greater SGM cultural competence. Greater number of SGM-specific training hours was associated with greater clinical preparedness and affirming behaviors.

Conclusion: Sociodemographic factors, lived experiences, and training matter for healthcare professional students’ preparedness in caring for SGM patients.

Lesbian, gay, bisexual, transgender, queer, and intersex (LGBTQI) people—broadly included within the umbrella of “sexual and gender minorities” (SGM)—have unique health and healthcare needs. SGM youth experience higher rates of family rejection, increased use of tobacco and other substances, more bullying, and higher suicide rates.1 A recent study reported that SGM people want their healthcare providers to be comfortable caring for them, knowledgeable about their healthcare needs, and avoid making assumptions.2 Yet healthcare professional student education on SGM health topics is sparse.3-6 With lesbian, gay, bisexual, and queer people comprising 3.5% of the US population, and transgender and intersex people comprising another 1.5%, it is critical for healthcare professional students to be clinically and culturally prepared to meet the needs of these patients.7-9

This study builds on prior research in the literature that explores the association of sociodemographic factors with healthcare professional student competence in caring for SGM patients.10,11 The purpose of the study was to identify factors associated with more SGM-affirming knowledge, attitudes, clinical preparedness, beliefs, and behaviors among a group of healthcare professional students to inform future educational interventions to improve clinical care for SGM patients. The null hypothesis was that sociodemographic and lived experiences would not predict differences in cultural competency constructs.

Materials and Methods


The sample for this study (N = 48) was a subset of healthcare professional students and faculty previously surveyed for another purpose.12 The primary study examined the effectiveness of an elective symposium on LGBTQI health on the knowledge, attitudes, clinical preparedness, beliefs, and behaviors of healthcare professional students at an urban university by comparing attendees (n = 29) to a control group (n = 134).12 The control group for the primary study was a convenience sample recruited via listservs within various healthcare professional schools at an urban university. The present sample (N = 48) was limited to students in the control group of the primary study who answered all 8 independent variables being explored via an online survey.

Participant characteristics are shown in Table 1. The sample was primarily white (65%), female (68.8%), and heterosexual (66.7%). The majority of students were medical students in clinical years of training (52.1%). Approximately 90% of participants reported being mostly or very liberal. Overall, the sample was more spiritual than religious and represented a variety of religions.

Ethical Review

The George Washington University Institutional Review Board determined this study to be exempt (#180645) under Department of Health and Human Services regulatory categories 2 and 4.


This exploratory study included 8 independent variables (Full Model): sexual orientation, sex assigned at birth, political affiliation, religiosity, spirituality, SGM affiliation (having friends or family or self-identifying as an SGM person), number of SGM patients seen in the past 6 months, and number of cumulative SGM-specific training hours. Parsimonious or Reduced Models were created that explained a meaningful (≥.15) amount of total variance across a sample of healthcare professional students in terms of 5 criterion variables that measured constructs related to cultural competence in caring for SGM patients. The 5 criterion variables (or cultural competency–related construct) are detailed under measures. Multiple linear regression was used to examine the Full Models to eliminate independent variables that did not explain a meaningful amount of variance for each construct measured. Reduced Models were reported to clarify what types of lived experiences were associated with Basic Knowledge, Affirming Attitudes, Clinical Preparedness, Beliefs, and Behaviors, respectively.


An online survey asked a total of 144 questions, 61 of which were included in this study. Items included 13 demographic and experience questions, the Lesbian, Gay, Bisexual, Transgender Development of Clinical Skills Scale (LGBT-DOCSS),13 and the Gay Affirming Practice Scale (GAPS).14


The LGBT-DOCSS is an 18-item scale with 3 subscales that measure constructs associated with self-reported competence in caring for SGM patients across interdisciplinary healthcare professionals.13 The scale has been tested for factor structure, reliability, and validity.13 In the original instrument, respondents rated their agreement with each item on a 7-point scale from strongly disagree (1) to strongly agree (7) for a total score ranging from 18 to 126 for the overall scale. Subscale ranges are Basic Knowledge (4-28), Attitudinal Awareness (7-49), and Clinical Preparedness (7-49). Total scores for the full scale and each subscale are intended to be tallied and then divided by the total number of items to obtain a mean score. Higher scores reflect greater self-reported competence in each domain.

In this study, the LGBT-DOCSS was altered by reducing response options from a 7-point to a 5-point scale and reversing directionality of the scale to ensure cognitive consistency of the directionality and range of response categories for all items of the survey. As recommended by Dillman,15 to provide a more authentic nonresponse option while retaining reasonable estimates of respondent attitudes, the middle answer option was moved to the far right to distinguish it as “Not sure” rather than neutral.16 One item in the factor analysis of the LGBT-DOCSS manuscript was different from the final instrument published13; therefore, both items were included. After correspondence with the scale author (M. Pratt-Chapman to M. Bidell, October 2018), however, only the correct item was used in this analysis. Subscales were tallied for composite scores with a range of 4 to 20 (Knowledge), 7 to 35 (Attitudes), and 7 to 35 (Clinical Preparedness). Higher scores reflect greater knowledge, more affirming attitudes, and greater clinical preparedness, respectively.


The GAPS is a 30-item scale designed to measure health practitioners’ beliefs and behaviors regarding care of gay and lesbian individuals.14 The instrument uses a 5-point Likert scale from strongly agree (5) to strongly disagree (1) for items 1 to 15 and from always (5) to never (1) for items 16 to 30. The directionality and scoring for items were retained from the original instrument with the neutral answer option shifted to the far right to allow for a genuine nonresponse option as with the prior 2 scales. The range of possible scores for each subscale is 15 to 75 with a higher score reflecting more affirming beliefs or behaviors, respectively. Crisp established construct validity and strong internal reliability for each subscale.14

Statistical Analysis

Data were accessed through the secure REDCap database and analyzed using SPSS 24. Since answers to the independent variables being tested were criteria for inclusion in the study, independent variables had no missing data but resulted in a limited sample size. Data for independent variables were not imputed due to the personal nature of sex assigned at birth, sexual orientation, religiosity, spirituality, and political affiliation—characteristics that are inherent to the nature of the respondent. Missing data for dependent variables were less than 5%. Based on Cheema,17 this low amount of missing data can be dealt with in numerous ways, including multiple imputation techniques or leaving data as missing. For this study, data were left as missing.

G*Power was used to conduct post hoc power analyses for all models, individual predictor variables within models, and model comparisons.18 Based on the post hoc power analyses, the secondary sample was underpowered (1-β <.80) for most models to explain a medium effect (f2 = .13) for α = .05 and for most individual predictors to detect a small effect (f2 = .02) for α = .05.19 For Reduced Models, power ranged from (1-β) = .36-.75 with all Reduced Models powered at (1-β) ≥.50. Because the sample was underpowered, meaningful variance (>.15) in the criterion variable explained by individual predictors and for each model were examined rather than statistical significance.19 However, statistical significance was also reported.

Multiple linear regression was used to test the value of an 8-variable model (Full Model) for each criterion variable. The 8 independent variables were sexual orientation, sex assigned at birth, political affiliation, religiosity, spirituality, SGM affiliation (identifying as or having a friend or family member who identifies as LGBTQ), number of SGM-specific training hours, and number of SGM patient interactions in the past 6 months. Statistical significance of independent variables within each model as well as percent of variance explained was examined. Using Cohen’s benchmarks for a small proportion of variance explained, any variable explaining >2% unique variance was included in the Reduced Model.19 Reduced Models were examined for statistical significance and proportion of variance explained based on Cohen’s benchmarks: small (R2 = .02), medium (R2 = .13), and large (R2 = .26).19 For all Reduced Models, interaction effects were examined by creating cross-product terms.20 Selection of final variables was based on model comparisons.20,21 Tolerance and variance inflation factor were checked for all Reduced Models to ensure that collinearity did not apply. Correlations of all independent variables and each criterion variable were also examined.

Descriptive and inferential statistics were reported. Ordinary least squares was used to test individual predictor variables. Multiple R was reported for correlation between the criterion variable and all predictors in each model. Multiple R2 was reported for percent variance in each criterion variable explained by all predictors in each model. Reduced Models were considered meaningful and parsimonious if there was no more than a 10% drop in total variance explained from the Full to the Reduced Model.


Reduced Models explained a statistically significant amount of variance for Basic Knowledge and Attitudinal Awareness subscales of the LGBT-DOCSS and for the Beliefs and Behaviors subscales of the GAPS (P ≤.05). The Reduced Model for the Clinical Preparedness subscale of the LGBT-DOCSS did not explain a statistically significant amount of variance.

Political affiliation was the most common predictor variable retained in the Reduced Models (Tables 3, 5, and 6) followed by religiosity (Tables 2 and 4) and SGM affiliation (Tables 2 and 5). Less religiosity, greater SGM affiliation, and greater number of SGM patients explained greater self-reported Basic Knowledge of SGM health (LGBT-DOCSS). Political affiliation was the only meaningful predictor of self-reported SGM-affirming attitudes as measured by the Attitudinal Awareness subscale of LGBT-DOCSS. Together, religiosity, spirituality, and number of SGM-specific health training hours explained a statistically insignificant, but meaningful amount of variance for self-reported Clinical Preparedness in caring for SGM patients (LGBT-DOCSS). Political affiliation and SGM affiliation together explained nearly half of the variance in self-reported beliefs about how providers should care for SGM patients as measured by the GAPS-Beliefs subscale. Together, sexual orientation, political affiliation, spirituality, and number of SGM training hours explained slightly more than half of variance in the sample as measured by the GAPS-Behavior subscale.


Four of the 5 Reduced Models explained a statistically significant amount of total variance for their respective criterion variables despite the small sample size. This means that sociodemographic factors, lived experiences, and amount of training in SGM-specific health matter a great deal when it comes to healthcare professional students’ overall sense of competence in caring for SGM patients.

Political affiliation—only 1 independent variable—explained nearly half of the total sample variance in self-reported attitudes about SGM patients and was included in more than half of the Reduced Models. It is important to note that the political affiliation variable was dichotomized to “liberal” versus “not liberal” by combining conservative, very conservative, neither liberal nor conservative, and apolitical into the “not liberal” category due to small sample sizes for each level. These results reinforce past research exploring the influence of political affiliation on attitudes toward SGM people in other populations.22-25

The association of political affiliation with healthcare professional student attitudes in this study is a challenging finding. Healthcare professional schools cannot and should not make acceptance into healthcare professional training subject to political affiliation. However, negative attitudes toward SGM patients should not be tolerated. This finding suggests that solutions are needed to bridge polarized social attitudes when it comes to patient care. Healthcare is a helping profession with a guiding value to “do no harm.” While social and political attitudes may vary widely among healthcare professionals and students, the principles of patient autonomy, medical and research beneficence, and justice can serve as an ethical framework for bridging sociopolitical divides to optimize the health and wellness of patients from diverse lived experiences. Future studies that examine ways to bridge political and social differences through exploration of shared professional values are needed.

The association of strong spirituality with more affirming clinical preparedness and behaviors is a novel finding and contrary to past research.26 In fact, this is the first known study to report the association of strong spirituality with greater self-reported clinical preparedness and more affirming clinical behaviors for SGM patients. It is important to interpret this finding with caution for several reasons: First, there was an interaction between spirituality and number of training hours on self-reported clinical behaviors. Second, definitions of spirituality vary, making it a complex construct to interpret. Third, social desirability bias may have played a role in self-reported scores. It is important to note that greater spirituality did not equate to greater religiosity or vice versa. These variables were negatively associated. Thus, less religiosity predicted more affirming attitudes toward SGM people, similar to findings in past studies.13,23,27,28 In past research, less conservative religion also has predicted less bias toward SGM people.22,27,29 Further exploration of the relationship between healthcare providers’ religiosity, spirituality, and attitudes toward SGM people is warranted.

The association of SGM-specific training and SGM affiliation with greater clinical preparedness and affirming behaviors is a critical finding that supports past research.4,13,22,23,27,30-41 Intentional design of curricula to include SGM content and exposure to diverse SGM patients are a necessary component of healthcare professional education and training. Educational interventions should consider student dialogue with SGM community members, faculty, and peers as one way to increase students’ sense of knowledge and to foster more affirming attitudes and beliefs about their SGM patients.

Past research has also found that younger age30 and white (versus nonwhite) race35,37,41 predicted more affirming attitudes toward SGM people. Factors predictive of greater SGM bias also include belief in traditional gender roles,22,42 acceptance of male aggressiveness,42 racist attitudes,22 lack of egalitarian humanism,22 rural residence,22 and lower educational attainment.22 Age was not selected as a variable for study in the present analysis, because there was little variability in the age of students. Race and sex assigned at birth were captured; however, race was not included in modeling, because nothing meaningful could be said about differences across racial groups given the sample size. Sex assigned at birth was included in the present analysis but did not predict a meaningful amount of variance in the sample. The other variables described above from past studies were not captured in data collection for the present study.

There were several key limitations in this study, including the small sample size and the nonrepresentative nature of the sample. The voluntary, opt-in recruitment approach may have resulted in respondents who were more likely to be interested in SGM health generally. Furthermore, the study was cross-sectional; therefore, results are only a snapshot in time and may not represent evolving student-reported knowledge, attitudes, clinical preparedness, beliefs, and behaviors over time. This sample also lacks representativeness in that it was strongly liberal. Future studies should consider oversampling conservative, male, nonwhite, and non-Christian healthcare professional students to allow for subgroup analyses of political affiliation, sex assigned at birth, race, and religion. However, while the sample size was small, findings were statistically significant—which means results are actually stronger than in a larger (powered) sample.43 Thus, while the findings cannot be assumed generalizable, the findings should be interpreted as valid for the sample studied. Finally, it is important to emphasize the exploratory nature of the study. While constructs were drawn from the literature, there was little prior research on which to test predetermined models for their predictive value.

Additional research studies in diverse settings with diverse samples are needed to confirm results reported from this study. Researchers can build on the present study by improving the psychometric rigor and availability of scales that measure health professional student clinical preparedness and behaviors. As theory and research on SGM clinical preparedness grows, confirmatory studies using more sophisticated modeling techniques—such as hierarchical modeling of theory- driven variables and mixed effects models—are warranted. Additional approaches to measure implicit bias and longitudinal clinical practices of student learners are also needed. Ultimately, the field will benefit from assessing clinical competence through objective instruments, not simply self-reported measures.


This exploratory study reinforces past research that has suggested that sociodemographic and lived experiences matter when it comes to healthcare provider competence in caring for SGM patients. The study contributes to the literature through the paradoxical finding that greater spirituality and less religiosity predicted more affirming attitudes toward SGM patients. Findings reinforce that personal exposure to and affiliation with SGM people as well as amount of SGM-specific curricula are meaningful predictors of clinical behavior and preparedness, respectively. Innovative educational approaches are needed to ensure that affirming care is provided to SGM patients regardless of the sociopolitical background of the provider by focusing on respect, justice, and beneficence as paramount to the delivery of quality healthcare.


The authors would like to acknowledge the following individuals who served on the corresponding author’s dissertation committee: Leslie Davidson, PhD, Chair of the Department of Clinical Research and Leadership at the George Washington University School of Medicine and Health Sciences, served as Chair of her dissertation committee. Brandi A. Weiss, PhD, guided the quantitative methods. Thank you also to dissertation readers Markus Bidell, PhD, and Lawrence Deyton, MD.


Funding: No funding was provided for this study. However, data capture was supported through the Clinical and Translational Science Institute at Children’s National (CTSI-CN) funded by the National Institutes of Health (NIH) Clinical and Translational Science Award (CTSA) Program, grant UL1TR001876. The CTSA program is led by the NIH’s National Center for Advancing Translational Sciences. The content of this website is solely the responsibility of the CTSI-CN and does not necessarily represent the official views of the NIH.

Disclosure statement: The authors declare no competing interests.

Data availability statement: Data are available upon request to the corresponding author.

Authors’ contributions: MPC conceptualized the study, collected and analyzed data, wrote the manuscript, and approved the final submission. JP reviewed the manuscript, provided feedback, and approved the final version.


  1. Hafeez H, Zeshan M, Tahir MA, et al. Health care disparities among lesbian, gay, bisexual, and transgender youth: a literature review. Cureus. 2017;9:e1184.
  2. Alpert AB, CichoskiKelly EM, Fox AD. What lesbian, gay, bisexual, transgender, queer, and intersex patients say doctors should know and do: a qualitative study. J Homosex. 2017;64:1368-1389.
  3. Obedin-Maliver J, Goldsmith ES, Stewart L, et al. Lesbian, gay, bisexual, and transgender-related content in undergraduate medical education. JAMA. 2011;306:971-977.
  4. Dowshen N, Gilbert K, Feiler A, Lee S. Transgender health education impact on medical student knowledge, skills and attitudes. J Adoles Health. 2013;52:S235.
  5. Burke SE, Dovidio JF, Przedworski JM, et al. Do contact and empathy mitigate bias against gay and lesbian people among heterosexual medical students? A report from the Medical Student CHANGE Study. Acad Med. 2015;90:645-651.
  6. Braun HM, Ramirez D, Zahner GJ, et al. The LGBTQI health forum: an innovative interprofessional initiative to support curriculum reform. Med Educ Online. 2017;22:1306419.
  7. Gates GJ. How Many People are Lesbian, Gay, Bisexual, and Transgender? The Williams Institute. 2011.
  8. Flores AR, Herman JL, Gates GJ, Brown TNT. How Many Adults Identify as Transgender in the United States? The Williams Institute. https://wil 2016.
  9. Intersex Campaign for Equality. How common is intersex? An explanation of the stats. 2020.
  10. McKelvey RS, Webb JA, Baldassar LV, et al. Sex knowledge and sexual attitudes among medical and nursing students. Aust N Z J Psychiatry. 1999;33:260-266.
  11. Sanchez NF, Rabatin J, Sanchez JP, et al. Medical students’ ability to care for lesbian, gay, bisexual, and transgendered patients. Fam Med. 2006;38:21-27.
  12. Pratt-Chapman ML, Phillips S. Health professional student preparedness to care for sexual and gender minorities: efficacy of an elective interprofessional learning intervention. J Interprof Care. 2019;34:418-421.
  13. Bidell MP. The Lesbian, Gay, Bisexual, and Transgender Development of Clinical Skills Scale (LGBT-DOCSS): establishing a new interdisciplinary self-assessment for health providers. J Homosex. 2017;64:1432-1460.
  14. Crisp C. The Gay Affirmative Practice Scale (GAP): a new measure for assessing cultural competence with gay and lesbian clients. Soc Work. 2006;51:115-126.
  15. Dillman DA. Mail and Internet Surveys: The Tailored Design Method. 2nd ed. New York: John Wiley & Sons; 2000.
  16. Schim SM, Doorenbox AZ, Miller J, Benkert R. Development of a cultural competence assessment instrument. J Nurs Meas. 2003;11:29-40.
  17. Cheema JR. Some general guidelines for choosing missing data handling methods in educational research. Journal of Modern Applied Statistical Methods. 2014;13(2):53-75.
  18. Faul F, Erdfelder E, Buchner A, Lang A-G. Statistical power analyses using G*Power 3.1: tests for correlation and regression analyses. Behav Res Methods. 2009;41:1149-1160.
  19. Cohen J. Statistical Power Analysis for the Behavioral Sciences. 2nd ed. Hillsdale, NJ: Lawrence Erlbaum Associates; 1988.
  20. Maxwell SE, Delaney HD. Designing Experiments and Analyzing Data: A Model Comparison Perspective. 2nd ed. New York, NY: Routledge; 2004.
  21. Kelley K, Maxwell SE. Multiple Regression. In: Hancock GR, Stapleton LM, Mueller RO, eds. The Reviewer’s Guide to Quantitative Methods in the Social Sciences. 2nd ed. New York, NY: Routledge; 2019.
  22. Morrison MA, Morrison TG. Development and validation of a scale measuring modern prejudice toward gay men and lesbian women. J Homosex. 2002;43:15-37.
  23. Norton AT, Herek GM. Heterosexuals’ attitudes toward transgender people: findings from a national probability sample of U.S. adults. Sex Roles. 2013;68(11):738-753.
  24. Ali N, Fleisher W, Erickson J. Psychiatrists’ and psychiatry residents’ attitudes toward transgender people. Acad Psychiatry. 2015;40:268-273.
  25. Pelle CD, Cerratti F, Di Giovanni P, et al. Attitudes towards and knowledge about lesbian, gay, bisexual, and transgender patients among Italian nurses: an observational study. J Nurs Scholarsh. 2018;50:367-374.
  26. Wilson CK, West L, Stepleman L, et al. Attitudes toward LGBT patients among students in the health professions: influence of demographics and discipline. LGBT Health. 2014;1:204-211.
  27. Cramer E. Effects of an educational unit about lesbian identity development and disclosure in a social work methods course. Journal of Social Work Education. 1997;33:461-472.
  28. Klotzbaugh R, Spencer G. Magnet nurse administrator attitudes and opportunities: toward improving lesbian, gay, bisexual, or transgender-specific healthcare. J Nurs Adm. 2014;44:481-486.
  29. Kissinger DB, Lee SM, Twitt L, Kisner H. Impact of family environment on future mental health professionals’ attitudes toward lesbians and gay men. J Homosex. 2009;56:894-920.
  30. Bidell MP. Addressing disparities: the impact of a lesbian, gay, bisexual, and transgender graduate counselling course. Counselling & Psychotherapy Research. 2013;13(4):300-307.
  31. Phelan SM, Burke SE, Hardeman RR, et al. Medical school factors associated with changes in implicit and explicit bias against gay and lesbian people among 3492 graduating medical students. J Gen Intern Med. 2017;32:1193-1201.
  32. Earnshaw VA, Jin H, Wickersham JA, et al. Stigma toward men who have sex with men among future healthcare providers in Malaysia: would more interpersonal contact reduce prejudice? AIDS Behav. 2016;20:98-106.
  33. Tucker A, Lih J, de Swardt G, et al. Efficacy of tailored clinic trainings to improve knowledge of men who have sex with men health needs and reduce homoprejudicial attitudes in South Africa. LGBT Health. 2016;3:443-450.
  34. Thomas JL, Scott LK, Brooks CM. Attitude change in a human sexuality course that de-emphasizes small group activities. Med Educ. 1980;14:254-258.
  35. Chng CL, Moore A. Can attitudes of college students towards aids and homosexuality be changed in six weeks? The effects of a gay panel. Health Values: Health Behavior, Education & Promotion. 1991;15(2):41-49.
  36. Green S, Dixon P, Gold-Neil V. The effects of a gay/lesbian panel discussion on college student attitudes toward gay men, lesbians, and persons with AIDS. Journal of Sex Education and Therapy. 1993;19(1):47-63.
  37. Black B, Oles T, Moore L. Homophobia among students in social work programs. Journal of Baccalaureate Social Work. 1996;2:23-41.
  38. Beagan BL, Fredericks E, Goldberg L. Nurses’ work with LGBTQ patients: “they’re just like everybody else, so what’s the difference?” Can J Nurs Res. 2012;44:44-63.
  39. Banwari G, Mistry K, Soni A, et al. Medical students and interns’ knowledge about and attitude towards homosexuality. J Postgrad Med. 2015;61:95-100.
  40. Fisher AD, Castellini G, Ristori J, et al. Who has the worst attitudes toward sexual minorities? Comparison of transphobia and homophobia levels in gender dysphoric individuals, the general population and health care providers. J Endocrinol Invest. 2017;40:263-273.
  41. Greene MZ, France K, Kreider EF, et al. Comparing medical, dental, and nursing students’ preparedness to address lesbian, gay, bisexual, transgender, and queer health. PLOS One. 2018;13:e0204104.
  42. Swank E, Raiz L. Explaining comfort with homosexuality among social work students: the impact of demographic, contextual, and attitudinal factors. Journal of Social Work Education. 2007;43(2):257-279.
  43. Friston K. Ten ironic rules for non-statistical reviewers. Neuroimage. 2012;61:1300-1310.
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