Gender Minorities in Simulation: A Mixed Methods Study of Medical School Standardized Patient Programs in the United States and Canada
Why this work is in the frame
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Bibliographic record
Abstract
Purpose A provider's ability to translate knowledge about transgender health to affirming patient care is key to addressing disparities. However, standardized patient (SP) programs have little published guidance for gender-affirming care or addressing disparities experienced by transgender and nonbinary patients. Method Between 2018 and 2019, we invited all 208 accredited US and Canadian medical schools to participate in a study to determine how gender minorities are represented in SP encounters. Responding programs (n = 59, response rate = 28%) that represented patients with diverse gender identities were invited to complete semistructured interviews about SP case content, impact, and barriers to this work. Discussions were analyzed using a modified grounded theory method. Results Fifty nine of 208 eligible programs (response rate = 28.3%) completed our survey and 24 completed interviews. More than half of programs used gender minority SPs (n = 35, 59.3%). More than half of the programs also reported portraying gender minority cases (n = 31, 52.5%). Interviewees described how effective SP simulation required purposeful case development, engaging subject matter experts with lived experience, and ensuring psychological safety of gender minority SPs. Barriers included recruitment, fear of disrespecting gender minority communities, and transphobia. Engaging gender minorities throughout case development, training, and implementation of SP encounters was perceived to reduce bias and stereotyping, but respondents unanimously desired guidance on best practices on SP methodology regarding gender identity. Conclusions Many programs have established or are developing SP activities that portray gender minority patients. Effective SP simulation hinges on authenticity, but the decisions around case development and casting vary. Specifically, programs lack consensus about who should portray gender minority patients. This research suggests that input from gender minority communities both to inform best practices at the macro level and in an ongoing advisory capacity at the program level will be essential to teach gender-affirming care.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it