Gender Differences in Emergency Medicine Attending Physician Comments to Residents: A Qualitative Analysis
Bibliographic record
Abstract
Importance: Prior studies have revealed gender differences in the milestone and clinical competency committee assessment of emergency medicine (EM) residents. Objective: To explore gender disparities and the reasons for such disparities in the narrative comments from EM attending physicians to EM residents. Design, Setting, and Participants: This multicenter qualitative analysis examined 10 488 narrative comments among EM faculty and EM residents between 2015 to 2018 in 5 EM training programs in the US. Data were analyzed from 2019 to 2021. Main Outcomes and Measures: Differences in narrative comments by gender and study site. Qualitative analysis included deidentification and iterative coding of the data set using an axial coding approach, with double coding of 20% of the comments at random to assess intercoder reliability (κ, 0.84). The authors reviewed the unmasked coded data set to identify emerging themes. Summary statistics were calculated for the number of narrative comments and their coded themes by gender and study site. χ2 tests were used to determine differences in the proportion of narrative comments by gender of faculty and resident. Results: In this study of 283 EM residents, of whom 113 (40%) identified as women, and 277 EM attending physicians, of whom 95 (34%) identified as women, there were notable gender differences in the content of the narrative comments from faculty to residents. Men faculty, compared with women faculty, were more likely to provide either nonspecific comments (115 of 182 [63.2%] vs 40 of 95 [42.1%]), or no comments (3387 of 10 496 [32.3%] vs 1169 of 4548 [25.7%]; P < .001) to men and women residents. Compared with men residents, more women residents were told that they were performing below level by men and women faculty (36 of 113 [31.9%] vs 43 of 170 [25.3%]), with the most common theme including lack of confidence with procedural skills. Conclusions and Relevance: In this qualitative study of narrative comments provided by EM attending physicians to residents, multiple modifiable contributors to gender disparities in assessment were identified, including the presence, content, and specificity of comments. Among women residents, procedural competency was associated with being conflated with procedural confidence. These findings can inform interventions to improve parity in assessment across graduate medical education.
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How this classification was reachedexpand
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".