Practical solutions for implementation of Transition to Practice curricula in a competency-based medical education model.
Bibliographic record
Abstract
Background: Although transition from residency to practice represents a critical learning stage, there is a paucity of literature to inform local curriculum development and implementation.Objectives: To describe local curriculum development for Transition to Practice (TTP) for use within a competency-based medical education model, including important content and suitable teaching and assessment strategies.
 Design: We reviewed the literature to construct a definition and develop initial curriculum content for TTP. We then gathered local residency program directors’ views on TTP content, teaching, and assessment via online survey and an international educational conference workshop.
 Results: We identified 21 important TTP content areas in the literature and analyzed 35 survey responses, representing 33 residency programs. Survey participants viewed Further sophistication of clinical skills, How to set up a practice, and Time management skills as the three most important content areas. Views on content importance varied by program. For learning and teaching strategies, most respondents preferred: assessing what residents could do, providing real-life practice opportunities, and offering workplace-based assessments.
 Conclusions: TTP curricula implementation should reflect nationally set, specialty-specific curriculum elements; locally developed priority content; and learning and teaching strategies. Individual learner needs and imminent practice context should guide faculty approaches to curriculum delivery.
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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 | 0.002 | 0.069 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.006 | 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".