Entrustable Professional Activities in Palliative Medicine: A Faculty and Learner Development Activity
Bibliographic record
Abstract
Background:Faculty development (FD) is critical to the implementation of competency-based medical education (CBME) and yet evidence to guide the design of FD activities is limited. Our aim with this study was to describe and evaluate an FD activity as part of CBME implementation. Methods:Palliative medicine faculty were introduced to entrustable professional activities (EPAs) and gained experience estimating a learner’s level of readiness for entrustment by directly observing a simulated encounter. The variation that was found among assessments was discussed in facilitated debrief sessions. Attitudes and confidence levels were measured 1 week and 6 months following debriefs. Results: Participants were able to use the EPA framework when estimating the learner’s readiness level for entrustment. Significant improvements in attitudes and level of confidence for several knowledge, skill, and behavior domains were maintained over time. Conclusions:Simulated direct observation and facilitated debriefs contributed to preparing both faculty and learners for CBME and EPA implementation.
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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 | 0.011 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".