Incidence of resident mistreatment in the learning environment across three institutions
Bibliographic record
Abstract
INTRODUCTION: Mistreatment in the learning environment is associated with negative outcomes for trainees. While the Association of American Medical Colleges (AAMC) annual Graduation Questionnaire (GQ) has collected medical student reports of mistreatment for a decade, there is not a similar nationally benchmarked survey for residents. The objective of this study is to explore the prevalence of resident experiences with mistreatment. METHODS: Residents at three academic institutions were surveyed using questions similar to the GQ in 2018. Quantitative data were analyzed based on frequency and Mann-Whitney U tests to detect gender differences. RESULTS: Nine hundred ninety-six of 2682 residents (37.1%) responded to the survey. Thirty-nine percent of residents reported experiencing at least one incident of mistreatment. The highest reported incidents were public humiliation (23.7%) and subject to offensive sexist remarks/comments (16.0%). Female residents indicated experiencing significantly more incidents of public embarrassment, public humiliation, offensive sexist remarks, lower evaluations based on gender, denied opportunities for training or rewards, and unwanted sexual advances. Faculty were the most frequent instigators of mistreatment (66.4%). Of trainees who reported experiencing mistreatment, less than one-quarter reported the behavior. CONCLUSION: Mistreatment in the academic learning environment is a concern in residency programs. There is increased frequency among female residents.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".