Leading from Behind: An Educational Intervention to Address Faculty and Learner Preparedness for Competence By Design in Psychiatry
Bibliographic record
Abstract
Purpose: Residency training programs across Canada are beginning to implement the Royal College of Physicians and Surgeons of Canada’s new Competence By Design (CBD) framework in medical education. The objective of the current research was to assess faculty members’ and learners’ understanding of, and preparedness for, the national shift to CBD in psychiatry before and after an educational intervention. Methods: The current research implemented a pre-test/post-test design to investigate faculty members’ and learners’ perceptions and attitudes towards competency-based medical education (CBME) and CBD before and after a one-hour educational session delivered by an expert on CBME. Results: Of the 104 session attendees, 83 (79.8%) completed the pre-survey and 80 (76.9%) completed the post-survey. Both groups reported a moderate level of baseline knowledge of CBME and CBD. Knowledge of CBME improved significantly for both faculty members ( p = 0.03) and learners ( p < 0.01) after the education session; however, only learners showed a significant increase in knowledge of the CBD framework following the education session ( p < 0.01). Further, only learners demonstrated a significant increase in perceived preparedness for CBD following the session ( p = 0.02). Conclusion: Overall, a brief, one-hour education session was at least somewhat effective at improving knowledge and preparedness for psychiatry’s transition to CBD. In order to facilitate the transition to CBD and to assist in the rollout of future policy changes, psychiatry departments should provide both faculty members and learners with educational sessions and resources prior to the policy implementation. Keywords: competency-based medical education, Competence By Design, faculty development, feedback, implementation, policy change
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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 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".