Perception of Medical Student Mistreatment: Does Specialty Matter?
Bibliographic record
Abstract
PURPOSE: Medical student mistreatment is pervasive, yet whether all physicians have a shared understanding of the problem is unclear. The authors presented professionally designed trigger videos to physicians from 6 different specialties to determine if they perceive mistreatment and its severity similarly. METHOD: From October 2016 to August 2018, resident and attending physicians from 10 U.S. medical schools viewed 5 trigger videos showing behaviors that could be perceived as mistreatment. They completed a survey exploring their perceptions. The authors compared perceptions of mistreatment across specialties and, for each scenario, evaluated the relationship between specialty and perception of mistreatment. RESULTS: Six-hundred fifty resident and attending physicians participated. There were statistically significant differences in perception of mistreatment across specialties for 3 of the 5 scenarios: aggressive questioning (range, 74.1%-91.2%), negative feedback (range, 25.4%-63.7%), and assignment of inappropriate tasks (range, 5.5%-25.5%) (P ≤ .001, for all). After adjusting for gender, race, professional role, and prior mistreatment, physicians in surgery viewed 3 scenarios (aggressive questioning, negative feedback, and inappropriate tasks) as less likely to represent mistreatment compared with internal medicine physicians. Physicians from obstetrics-gynecology and "other" specialties perceived less mistreatment in 2 scenarios (aggressive questioning and negative feedback), while family physicians perceived more mistreatment in 1 scenario (negative feedback) compared with internal medicine physicians. The mean severity of perceived mistreatment on a 1 to 7 scale (7 most serious) also varied statistically significantly across the specialties for 3 scenarios: aggressive questioning (range, 4.4-5.4; P < .001), ethnic insensitivity (range, 5.1-6.1; P = .001), and sexual harassment (range, 5.5-6.3; P = .004). CONCLUSIONS: Specialty was associated with differences in the perception of mistreatment and rating of its severity. Further investigation is needed to understand why these perceptions of mistreatment vary among specialties and how to address these differences.
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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 | 0.003 | 0.029 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.003 | 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 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".