Implementation of competence by design in Canadian neurosurgery residency programs*
Bibliographic record
Abstract
The Royal College of Physicians and Surgeons of Canada (RCPSC) recently redesigned the Canadian neurosurgery residency training curriculum by implementing a competency-based model of training known as Competence by Design (CBD) centered around the assessment of Entrustable Professional Activities (EPAs). This sequential explanatory mixed-methods study evaluated potential benefits and pitfalls of CBD in Canadian neurosurgery residency education. Two four-month interval surveys were distributed to all Canadian neurosurgery residents participating in CBD. The surveys assessed important educational components: CBD knowledge of key stakeholders, potential system barriers, and educational/psychological impacts on residents. Paired t-tests were done to assess changes over time. Based on longitudinal survey responses, semi-structured interviews were conducted to investigate in-depth residents’ experience with CBD in neurosurgery. The qualitative analysis followed an explanatory approach, and a thematic analysis was performed. Surveys had 82% average response rate (n = 25). Over time, most residents self-reported that they retrospectively understood concepts around CBD intentions (p = 0.02). Perceived benefits included faculty evaluations with more feedback that was clearer and more objective (53% and 51%). Pitfalls included the amount of time needed to navigate through EPAs (90%) and residents forgetting to initiate EPA forms (71%). There was no significant change over time. During interviews, five key themes were found. Potential solutions identified by residents to enhance their experience included learning analytics data availability, mobile app refinement, and dedicated time to integrate EPAs in the workflow. This study was the first to assess resident-perceived benefits and pitfalls of the neurosurgery CBD training program in an educational framework context. In general, residents believed that theoretical principles behind CBD were valuable, but that technological ability and having enough time to request EPA assessments were significant barriers to success. Long-term studies are required to determine the definitive outcomes of CBD on residents’ performance and ultimately, on patient care.
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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 | 0.040 | 0.046 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.008 | 0.006 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| 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".