Senior medical students' appraisal of CanMEDS competencies
Bibliographic record
Abstract
CONTEXT: In 2003 the Dutch Central College of Medical Specialties presented guidelines for the modernisation of all medical specialty training programmes in the Netherlands. These guidelines are based to a large extent on the CanMEDS (Canadian Medical Education Directives for Specialists) 2000 model, which defines 7 roles for medical specialists. This model was adjusted to the Dutch situation. The roles were converted to 7 fields of competency: Medical Performance; Communication; Collaboration; Knowledge and Science; Community Performance; Management, and Professionalism. OBJECTIVE: As changes in postgraduate training will probably be most effective if future trainees recognise their value, we set out to determine how senior medical students rated these fields of competency in terms of their importance. METHODS: We carried out a study at University Medical Centre (UMC) Utrecht, the Netherlands, in which 80 Year 6 medical students answered a questionnaire in which they rated the importance of each of 28 key competencies within the 7 competency fields. RESULTS: Although all key competencies were regarded as important (averages > or = 3.8), Professionalism and Communication scored highest on the student ratings. Management was assessed as least important. CONCLUSIONS: It is interesting that medical students acknowledged the importance of competencies other than those involving medical expertise and performance. It confirms the opinion that educating doctors is currently viewed as much more than providing theoretical and clinical knowledge and skills. The CanMEDS framework is appreciated by Dutch medical students. The fact that all competencies are seen as important adds to their face validity and therefore to their usefulness as a basis for postgraduate training.
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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 | 0.023 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".