LGBTQ+ individuals are not explicitly represented in emergency medicine simulation curricula

Background Medical educational societies have emphasized the inclusion of marginalized populations, including the lesbian, gay, bisexual, transgender and queer (LGBTQ+) population, in educational curricula. Lack of inclusion can contribute to health inequality and mistreatment due to unconscious bias. Little didactic time is spent on the care of LGBTQ+ individuals in emergency medicine (EM) curricula. Simulation based medical education can be a helpful pedagogy in teaching cross-cultural care and communication skills. In this study, we sought to determine the representation of the LGBTQ+ population in EM simulation curricula. We also sought to determine if representations of the LGBTQ+ population depicted stigmatized behavior. Methods We reviewed 971 scenarios from six simulation case banks for LGBTQ+ representation. Frequency distributions were determined for major demographic variables. Chi-Squared or Fisher’s Exact Test, depending on the cell counts, were used to determine if relationships existed between LGBTQ+ representation and bank type, author type, and stigmatized behavior. Results Of the 971 scenarios reviewed, eight (0.82%) scenarios explicitly represented LGBTQ+ patients, 319 (32.85%) represented heterosexual patients, and the remaining 644 (66.32%) did not specify these patient characteristics. All cases representing LGBTQ+ patients were found in institutional case banks. Three of the eight cases depicted stigmatized behavior. Conclusions LGBTQ+ individuals are not typically explicitly represented in EM simulation curricula. LGBTQ+ individuals should be more explicitly represented to reduce stigma, allow EM trainees to practice using gender affirming language, address health conditions affecting the LGBTQ+ population, and address possible bias when treating LGBTQ+ patients.


Introduction
Over the past decade, medical education societies have called for the development of curricula to address the care of marginalized populations, including patients identifying as part of the lesbian, gay, bisexual, transgender, and queer (LGBTQ+) community [1][2][3][4] .The LGBTQ+ community faces unique challenges when interacting with the healthcare system, including overt discrimination, implicit bias, microaggressions and disparities in mental and physical health 5,6 .Moreover, LGBTQ+ medical students are subject to higher levels of mistreatment during their training than their straight counterparts 7 .
Racial/ethnic and sex/gender curricular biases are well documented [8][9][10][11][12] .These biases include omission of people of color and women from curricula, imbalance in the presentation of issues, and ignoring inequalities in health and illness 9 .Underrepresentation of LGBTQ+ individuals and families in educational materials can contribute to unconscious biases impacting both patients and medical trainees by centralizing heteronormativity and contributing to the isolation and "invisibility" of LGBTQ+ individuals 8,9 .When the LGBTQ+ population is represented in case-based curricula, there is a documented trend to perpetuate stigma by emphasizing associations between the LGBTQ+ community and sexually transmitted illnesses such as HIV/AIDS 8 .Medical education initiatives have been instrumental in advocating for the equitable treatment of LGBTQ+ patients and inclusivity in medical training environments 2 .Despite significant progress, the median time spent addressing LGBTQ+ health in United States and Canadian medical schools is only five hours across the entire curriculum 13 .Further, two-thirds of medical students rate their LGBTQ+-related curricula as fair, poor, or very poor 14 .A 2014 survey of emergency medicine (EM) residencies found that only 33% of programs incorporated topics of LGBTQ+ health in their curricula and spent an average of 45 minutes on this subject 15 .
Simulation-based medical education (SBME) can be a powerful way to incorporate LGBTQ+ healthcare and inclusivity in both undergraduate and graduate medical education.SBME fosters active learning while allowing trainees to practice skills and learn from mistakes without risk of adverse effects on patients 16 .EM residency curricula place an increasing emphasis on simulation as a pedagogic tool 17 , and the Accreditation Council for Graduate Medical Education (ACGME) has endorsed simulation as an important modality to teach patient care, medical knowledge, interpersonal and communication skills, and professionalism 18 .Interactive workshops and simulations can improve the delivery of cross-cultural healthcare 19,20 , and can increase the knowledge base related to the care of transgender patients 21,22 .
In this study, we sought to assess the representation of the LGBTQ+ population in EM simulation curricula.Specifically, we were interested in the extent to which EM simulation scenarios are explicitly inclusive of the LGBTQ+ population and whether the inclusion of LGBTQ+ individuals in simulated patient encounters centers around stigmatized diagnoses and behaviors.

Methods
The study authors reviewed 971 unique scenarios from six different simulation case banks.Three case collections were obtained from publicly available educational resources: MedEdPortal 23 , the Council of Residency Directors in EM (CORD) simulation case bank 24 and EM Sim Cases 25 .These resources were chosen for their popularity, 26 endorsement by professional societies 24 , and use of peer review.The MedEdPortal cases were identified by performing an advanced search of titles containing the words "emergency medicine" and "simulation" in the summer of 2021.In addition to the national resources, we were able to access a convenience sample of three private institutional case banks associated with residency training programs, one located in the northeast region of the USA and two on the west coast.Each of these programs has a large simulation training center.These included banks from two four-year programs and one three-year program.Permission to use the banks was obtained from the relevant organizations, departments, and institutions prior to analysis.
The simulation cases in each case bank were reviewed for LGBTQ+ representation.Coding guidelines were delineated prospectively in a data dictionary and the authors arbitrated collaboratively any ambiguity or question pertaining to the data dictionary until consensus was achieved prior to any data analysis.LGBTQ+ representation in simulated scenarios can be explicit delineation of patient sexual or gender orientation in case scripts such as "the patient is a male to female transwoman," or implicitly in depicting a romantic or familial relationship such as "the patient asks the trainee to notify his husband."In some instances, particularly in pediatric scenarios, sexual diversity can be represented by family members accompanying the patient.For example, "the patient is a six-week-old male accompanied by his mothers."Accordingly, demographic and behavioral variables coded were patient sexual orientation, relationship type depicted, gender identity, diagnosis, and behavioral concerns (such as intoxication, violence, or multiple sexual partners).When no sexual orientation or relationship was specified, the scenario was coded as "not specified."In contrast, when gender identity was not specified, the authors assumed a cis-gender patient.This assumption was based on common descriptions of patients in the English language in which cis-gender identity is not typically specified in medical case presentations though the cis-gender identity is implicit whereas trans identities are typically explicitly stated.Each case was coded by a single reviewer and arbitrated with another reviewer in cases with unclear language.All scenarios identified as depicting an LGBTQ+ patient or relationship were analyzed for stereotyping or stigmatizing diagnoses and behaviors.
The primary outcome measure was the number of simulation cases explicitly representing the LGBTQ+ population.Additional outcomes included assessment of whether cases representing the LGBTQ+ population depicted stigmatized diagnoses or behaviors.
Frequency distributions were determined for major demographic variables.Chi-Squared or Fisher's Exact Test, depending on the cell counts, were used to determine if relationships existed between LGBTQ+ representation and bank type, author type, and behavioral concerns and p<.05 was deemed significant.This study was reviewed by our institutional review board and was determined to not involve human subjects.

Results
Of the 971 scenarios reviewed, eight (0.82%) scenarios explicitly represented LGBTQ+ patients, 319 (32.85%) specified or implied through family affiliations that the patient was heterosexual, and the remaining 644 (66.32%) did not specify these patient characteristics 27 .No additional LGBTQ+ representation was identified when looking at other relationships depicted in scenarios, such as the parents of simulated pediatric patients.Scenario characteristics including LGBTQ+ representation, bank type, and case author type are summarized in Table 1.
Of the eight scenarios representing LGBTQ+ patients, seven specifically represented gay men and one represented a male bisexual patient.No lesbian or transgender patients were specifically represented.The diagnoses and behavioral descriptions of the eight scenarios representing LGBTQ+ patients are specified in Table 2.All eight cases representing LGBTQ+ patients were found in institutional case banks (p=0.0035).There were no significant relationships between LGBTQ+ representation nd author type.

Discussion
Although medical educational societies stress the importance of responsiveness to diverse patient populations in EM medical education attention to the LGBTQ+ population in EM training curricula remains limited 14,15 .The ACGME has determined that respect and responsiveness to diverse populations is a core competency amongst all physicians and must be integrated into training curricula 3 .Survey data, which likely underrepresents the true LGBTQ+ population, suggests that greater than 7% of the US population belongs to this group 28 .In our analysis, only 0.82% of cases explicitly represented LGBTQ+ individuals illustrating that LGBTQ+ individuals are not typically intentionally represented in the EM simulation curricula reviewed.
Lesbians and transgender individuals are not represented at all in our data set.Despite decades of calls for inclusion of LGBTQ+ issues in medical curricula, and the effectiveness of simulation in teaching cross-cultural care, writers at all levels of training are not writing this population into their scripts.
Transgender health is an especially neglected topic.
The majority of scenarios reviewed did not specify or imply the sexual orientation or gender identity of simulated patients at all.As SBME continues to be an integral part of EM education, lack of representation of the LGBTQ+ population in simulated patient encounters has the potential to reinforce unconscious assumptions of heterosexual normativity and to reinforce the invisibility felt by LGBTQ+ individuals in healthcare and medical training 5-9 .Our results indicate that there is an opportunity for future authors to intentionally represent the LGBTQ+ population and to incorporate inclusivity in the structure of SMBE.Other structural components of EM education such as case conferences and question banks may be a key area of future investigation into ways to improve LGBTQ+ inclusivity in EM training.
The number of cases explicitly representing the LGBTQ+ population was not sufficient to determine whether this population is being used to depict stigmatized behaviors.Additional work with a larger sample size would be necessary to determine if stigmatized behaviors and diagnoses such as drug use and sexually transmitted illnesses are associated with LGBTQ+ representation.
Our analysis illustrates that LGBTQ+ individuals are not typically explicitly represented in EM simulation curricula.We recommend that EM curricular directors recognize the importance of simulation in teaching issues related LGBTQ+ health to trainees.We suggest that simulation scenarios should be written to allow trainees to practice using gender affirming language, recognize and treat health conditions affecting the LGBTQ+ population, and address possible bias when treating LGBTQ+ patients.Particular attention should be given to creating simulated encounters focused on transgender healthcare, as the use of gender affirming medications and procedures can have important implications when transgender patients present to the emergency department.Finally, we recommend that more attention be paid to representing LGBTQ+ individuals across a variety of simulated encounters in order to decrease the stigma associated with implied heteronormativity and decrease the invisibility felt by LGBTQ+ trainees.
Our study is limited by the use of simulation databases that we were able to access, particularly when considering the vast number of private institutional simulation banks.This introduces selection bias.There may be more inclusive simulation banks we were unaware of.Simulation case banks are inherently variable, are not standardized and may be modified over time.Further, because of the scant number of scenarios in which LGBTQ+ identity is specified, we are not able to draw conclusions about whether these cases disproportionately depict stigmatized diagnoses or behaviors.Finally, because not all scenarios explicitly specify the sexual or gender identity of the patients, we make assumptions about implied heteronormativity in drawing our conclusions.

Conclusions
LGBTQ+ individuals are not typically explicitly represented in EM simulation curricula.
LGBTQ+ individuals should be more explicitly represented to reduce stigma, allow EM trainees to practice using gender affirming language, address health conditions affecting the LGBTQ+ population, and address possible bias when treating LGBTQ+ patients.More study is needed to determine if SMBE cases representing the LGBTQ+ population disproportionally depicts stigmatized behaviors and diagnoses.With a 43% response rate, 75% of programs offered education content on LGBTQ health.This shows improvement over the previous study.Can be included to make the intro more relevant without hindering the purpose of the study.

Methods
1. Good description of the data dictionary development, though the language was a bit dense and can be simplified somewhat.E.g. graph 2, line 1-3 is unnecessarily dense as it essentially describes the collaborative development of a data dictionary through iterative consensus.The data dictionary is not available in the appendix and would be needed to replicate this study fully.
2. Graph 2, last line: there is no description of how the analysis for stereotyping or stigmatizing diagnoses was to be done.Though there was not enough data to allow for this analysis, it would be helpful is a brief description of these methods would be included for reproducibility in other data sets.
3. Graph 4: can the authors expand on the choice of statistical test beyond "depending on cell counts".This is an appropriate test to compare data set distribution, but the choice of test was unclear.I think I know what the authors were getting at, but a clear description of how the tests would be chosen would be helpful for reproduction.

Well reported, clear and concise.
2. There is no mention of the statistical findings for a relationship between bank type and behavioral concerns as outlined in the methods, only commented on the author.This is commented on in the discussion but not presented in results.
3.There is also no mention of what statistical method was chosen, as it was either going to be Chi Squared or Fisher Exact.Even if null result, can this be reported for completeness?Discussion 1. Graph 1 line 1 and 2 -there is a missing comma after "EM medical education".Sentence is hard to read as a result.3. Fully support recommendations, great list.May include a research oriented recommendation to better characterize stigma in simulated encounters with LGBTQ populations.This is included in the conclusions but not discussions.

Daniel J. Egan
Harvard Affiliated Emergency Medicine Residency, Boston, Massachusetts, USA Thanks for your work on this important topic.This study represents an analysis of publicly available simulation cases in emergency medicine as well as a small cohort of institutional-based curricula.The largest limitation of the study is the fact that we do not know what is happening locally in residency programs who may be more inclusive and not publishing their simulation curricula.I suspect there are more sites where this is included, but not published given the lack of available locations to publish these type of cases on a regular basis.The CORD database is somewhat outdated and likely not having regular updates.It would be helpful in all of your simulation cases you evaluated to identify when they were submitted if possible given the more recent attention to themes of diversity and inclusive language.I think that your conclusion might be slightly overstated by making the generalization that the LGBTQ population is not represented in curricula.I think you need to temper this slightly to clarify that this is only in the cases to which you had access.
In your introduction section, there is a more recent reference related to the curricula of LGBTQ+ health that was updated by the same author group you cite as reference #15 which has a 2020 survey result comparing the change over time (Refer ref [1]).Would recommend that you update this to reflect this more recent data.You could also consider Regarding your method of identifying stereotypic or stigmatizing diagnoses and behaviors, how did your group come to consensus on what would be identified?I wonder if you considered having two reviewers given that this might be less obvious than the explicit statements on gender or sexual orientation?Additionally, you could consider a spot check of a second reviewer in order to demonstrate the validity of the abstraction.The discussion section is particularly strong as it relates to invisibility and the support of heteronormative assumptions.While you did the analysis forward (meaning looked at identification of LGBTQ+ people and behaviors), it would be curious if there were cases specific to some of the more biased behaviors you mention.For example, were there a number of HIV/AIDS or STI cases in the simulation cases you reviewed that did not have the patient identifying as a gay or bisexual man?This might be an interesting alternative approach to suggest that perhaps there was intentionality in not using this group to represent the disease which one could argue may be a step in the right direction.

Reviewer Expertise:
LGBTQ+ education for paediatric staff I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard, however I have significant reservations, as outlined above.

2 .
Graph 1 line 5: The citation only lists sexual orientation prevalence and transgender and gender diverse populations would be helpful to highlight, especially since they were not found in any of the simulations and the authors comment on this important need.Herman et al,2022 [Ref 2] and Meerwijk and Sevelius [Ref 3] are 2 possibilities.

References 1 .
Moll J, Vennard D, Noto R, Moran T, et al.: The prevalence of lesbian, gay, bisexual, and transgender health education and training in emergency medicine residency programs: Where are we now?.AEM Educ Train.2021; 5 (2): e10580 PubMed Abstract | Publisher Full Text Is the work clearly and accurately presented and does it cite the current literature?YesIs the study design appropriate and does the work have academic merit?YesAre sufficient details of methods and analysis provided to allow replication by others?YesIf applicable, is the statistical analysis and its interpretation appropriate?YesHave any limitations of the research been acknowledged?YesAre all the source data underlying the results available to ensure full reproducibility?PartlyAre the conclusions drawn adequately supported by the results?YesCompeting Interests: No competing interests were disclosed.Reviewer Expertise: Medical education, LGBT healthI confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard.Are all the source data underlying the results available to ensure full reproducibility?No source data requiredAre the conclusions drawn adequately supported by the results?YesCompeting Interests: No competing interests were disclosed.