Get Over It: Surgical Residents’ Responses to Simulated Harassment. A Multi Method Study
Bibliographic record
Abstract
OBJECTIVE: This study examined the response strategies of Surgery residents as bystanders to harassment in a simulated clinical environment, their alignment with the bystander intervention model, and the motivations behind their actions. DESIGN: Participants watched an educational video on harassment and ways to address it prior to undergoing a simulated clinical scenario where they witnessed a senior resident harassing a medical student. The study used audio-video recordings of the simulations to capture and analyze residents' verbal and nonverbal responses to harassment. Frequencies from deductive thematic analysis were used for descriptive analysis, and nonparametric chi-square tests. Audio recordings of debriefings following simulations were also analyzed using deductive thematic analysis to explore residents' motivations behind their responses. SETTING: The study was conducted in a controlled environment at McGill University's Steinberg Centre for Simulation and Interactive Learning (Montreal, Canada). PARTICIPANTS: Participants included 32 Surgery residents completing the simulation as part of their Objective Structured Clinical Examinations. 28 residents provided usable data for analysis. RESULTS: Residents used passive responses significantly more frequently than other responses throughout the simulation, especially in reaction to harassment. Analysis revealed that residents often delayed intervention, opting to remain passive or reassuring the victim rather than confronting the harasser. Debriefing showed that some residents intervened to denounce the SR's behavior or support the MS, while others hesitated due to discomfort with power dynamics, fear of repercussions, or uncertainty about addressing the situation CONCLUSIONS: The study found that Surgery residents exhibit a tendency towards passive bystander responses in the face of harassment highlighting the need for targeted educational strategies to address power dynamics, build confidence in bystander intervention, and promote proactive responses to harassment in clinical training. Future research should explore similar dynamics across different medical professionals and consider intersectional factors to enhance antiharassment initiatives in 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 | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 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".