Lesbian, Gay, Bisexual, and Transgender Patient Care: Medical Students' Preparedness and Comfort
Bibliographic record
Abstract
UNLABELLED: Phenomenon: Lesbian, gay, bisexual, and transgender (LGBT) individuals face significant barriers in accessing appropriate and comprehensive medical care. Medical students' level of preparedness and comfort caring for LGBT patients is unknown. APPROACH: An online questionnaire (2009-2010) was distributed to students (n = 9,522) at 176 allopathic and osteopathic medical schools in Canada and the United States, followed by focus groups (2010) with students (n = 35) at five medical schools. The objective of this study was to characterize LGBT-related medical curricula, to determine medical students' assessments of their institutions' LGBT-related curricular content, and to evaluate their comfort and preparedness in caring for LGBT patients. FINDINGS: Of 9,522 survey respondents, 4,262 from 170 schools were included in the final analysis. Most medical students (2,866/4,262; 67.3%) evaluated their LGBT-related curriculum as "fair" or worse. Students most often felt prepared addressing human immunodeficiency virus (HIV; 3,254/4,147; 78.5%) and non-HIV sexually transmitted infections (2,851/4,136; 68.9%). They felt least prepared discussing sex reassignment surgery (1,061/4,070; 26.1%) and gender transitioning (1,141/4,068; 28.0%). Medical education helped 62.6% (2,669/4,262) of students feel "more prepared" and 46.3% (1,972/4,262) of students feel "more comfortable" to care for LGBT patients. Four focus group sessions with 29 students were transcribed and analyzed. Qualitative analysis suggested students have significant concerns in addressing certain aspects of LGBT health, specifically with transgender patients. Insights: Medical students thought LGBT-specific curricula could be improved, consistent with the findings from a survey of deans of medical education. They felt comfortable, but not fully prepared, to care for LGBT patients. Increasing curricular coverage of LGBT-related topics is indicated with emphasis on exposing students to LGBT patients in clinical settings.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".