How to assess communication, professionalism, collaboration and the other intrinsic CanMEDS roles in orthopedic residents: use of an objective structured clinical examination (OSCE)
Bibliographic record
Abstract
BACKGROUND: Assessing residents' understanding and application of the 6 intrinsic CanMEDS roles (communicator, professional, manager, collaborator, health advocate, scholar) is challenging for postgraduate medical educators. We hypothesized that an objective structured clinical examination (OSCE) designed to assess multiple intrinsic CanMEDS roles would be sufficiently reliable and valid. METHODS: The OSCE comprised 6 10-minute stations, each testing 2 intrinsic roles using case-based scenarios (with or without the use of standardized patients). Residents were evaluated using 5-point scales and an overall performance rating at each station. Concurrent validity was sought by correlation with in-training evaluation reports (ITERs) from the last 12 months and an ordinal ranking created by program directors (PDs). RESULTS: Twenty-five residents from postgraduate years (PGY) 0, 3 and 5 participated. The interstation reliability for total test scores (percent) was 0.87, while reliability for each of the communicator, collaborator, manager and professional roles was greater than 0.8. Total test scores, individual station scores and individual CanMEDS role scores all showed a significant effect by PGY level. Analysis of the PD rankings of intrinsic roles demonstrated a high correlation with the OSCE role scores. A correlation was seen between ITER and OSCE for the communicator role, while the ITER medical expert and total scores highly correlated with the communicator, manager and professional OSCE scores. CONCLUSION: An OSCE designed to assess the intrinsic CanMEDS roles was sufficiently valid and reliable for regular use in an orthopedic residency program.
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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 | 0.010 | 0.030 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.001 | 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".