Using an objective structured clinical examination (OSCE) to assess multiple physician competencies in postgraduate training
Bibliographic record
Abstract
BACKGROUND: Competency-based models of medical education require reliable and valid assessment of multiple physician roles. AIMS: To develop and evaluate an objective structured clinical examination (OSCE) designed to assess 7 physician competencies (CanMEDS Roles). METHODS: Twenty four candidates from 4 neonatal-perinatal medicine training programs participated in a 10-station OSCE. Ten 5-point rating scales were developed and used to assess the CanMEDS Roles of Medical Expert, Communicator, Collaborator, Manager, Health Advocate, Scholar and Professional. Three descriptors of performance anchored the ratings. For each station, examiners completed appropriate CanMEDS ratings, a station-specific binary checklist and an overall process-related global rating. Trained standardized patients (SP) and standardized health professionals (SHP) completed rating scales that assessed verbal and non-verbal expression, empathy and coherence as well as the overall global rating. RESULTS: Each station incorporated 3-5 physician Roles. Interstation alpha was 0.80 for checklist scores and 0.88 for examiners' overall global rating. Median interstation alpha for individual CanMEDS ratings was 0.72 (range 0.08-0.91). There were significant correlations between examiner Medical Expert scores and SP/SHP overall global scores and between examiner Communicator scores and 4 SP/SHP assessments of communication skills. Second year trainees' CanMEDS scores for each competency were significantly higher than those of first year trainees (p < 0.05). CONCLUSIONS: The OSCE may be useful as a reliable and valid method of simultaneously assessing multiple physician competencies.
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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 | 0.006 | 0.010 |
| 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 | 0.001 |
| 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".