Exploring Mistreatment of Medical Students by Patients: A Qualitative Study
Bibliographic record
Abstract
PURPOSE: Mistreatment of medical students by patients has not been qualitatively explored in the literature. The authors sought to develop a rich understanding of the impact and consequences of medical students' experiences of mistreatment by patients. METHOD: This exploratory descriptive qualitative study was conducted at a large Canadian medical school from April-November 2020. Fourteen medical students were recruited for semistructured interviews. Students were asked about their experiences of mistreatment by patients and how they responded to these experiences. Transcripts were thematically analyzed using an inductive approach, and the authors interwove critical theory into their conceptual interpretation of the data. RESULTS: Fourteen medical students (median age = 25.5; 10, 71.4% self-reported male; 12, 85.7% self-identified visible minority) participated in this study. Twelve (85.7%) participants had personally experienced patient mistreatment and 2 (14.3%) had witnessed mistreatment of another learner. Medical students described being mistreated by patients based on their gender and race/ethnicity. Although all participants were aware of the institution's official mechanism for reporting mistreatment, none filed an official report. Some participants described turning to their formal (faculty members and residents) and informal (family and friends) social supports to cope with mistreatment by patients. Participants described resenting and avoiding patients who mistreated them and struggling to maintain empathy for, openness to, and overall ethical engagement with discriminatory patients. Students often described a need to be stoic toward their experiences of mistreatment by patients, often seeing it as their "professional duty" to overcome and thus suppress the negative emotions associated with mistreatment. CONCLUSIONS: Medical schools must proactively develop multifaceted mechanisms to support medical students who experience mistreatment by patients. Future research can further uncover this neglected dimension of the hidden curriculum to better develop responses to incidents of mistreatment that commit to antiracism, antisexism, patient care, and learner care.
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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 | 0.017 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.012 | 0.012 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.002 | 0.003 |
| 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".