Patients' perspectives on medical students' professionalism: Blind spots and opportunities
Bibliographic record
Abstract
BACKGROUND: Research has acknowledged the value of patients as essential stakeholders in medical education, yet educators have not adequately incorporated patients' perspectives into medical students' developing professionalism. Our purpose was to explore patients' perceptions of professional behaviour in medical students as a first step to considering patients' potential roles in assessing professionalism. METHODS: Building on the existing framework of the 'disavowed curriculum', we used a constructivist grounded theory approach to interview and analyse data from 19 patients (11 W, 8 M) at one urban hospital. Each participant watched five video scenarios that depict professionally challenging situations commonly faced by medical students, after which they were asked to put themselves in the position of both the patient and the student depicted in each scenario, and to discuss what they felt would be appropriate or inappropriate behaviours from each perspective. RESULTS: Patients' responses replicated all elements of the disavowed curriculum, including principles of professionalism, the student's affect or internal factors, and potential implications of actions. Their responses reflected avowed, unavowed and disavowed rationales. Participants also identified novel principles, including hide dissension in the ranks, respect privacy, advocate for yourself and have trust in the system. Patients conveyed an understanding of the multiple competing factors students must balance (e.g., providing optimal care while maximising educational opportunities) and appeared to empathise with some of the pressures students face. CONCLUSIONS: Our findings point to significant blind spots in previous research based on faculty and student perspectives of professionalism. Knowing what patients perceive as important will allow educational and assessment efforts to be refined to reflect their values. Our work begins the process of understanding how best to include patients in the assessment of medical learners.
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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 | 0.006 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.013 | 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".