Implementing entrustable professional activities: Practical lessons and legal considerations from an international interview study
Bibliographic record
Abstract
Purpose Entrustable professional activities (EPAs) provide a framework for supervising and assessing readiness for independent practice in postgraduate medical education. Their implementation has raised concerns about legal liability. This study explored practical and legal implications of EPA implementation across international contexts.Methods Fifteen participants from various specialties and 12 countries across six continents, all involved in EPA implementation, participated in qualitative semi-structured interviews. Interviews focused on accountability, competence assessment, and legal considerations. Thematic analysis was conducted.Results Five themes were identified: (1) Shifting accountability: EPAs shift accountability to trainees as competence increases, though supervision remains essential; (2) Sharing responsibilities: EPAs support role clarity and shared responsibility, with autonomy varying by setting; (3) Ascertaining competence: EPAs offer a transparent framework for competence assessment; (4) (Mis-)conceptions of legal consequences: legal concerns were largely unfounded as supervisors were still viewed as legally accountable; and (5) Context matters: implementation is shaped by institutional, regulatory, and cultural contexts, requiring local adaptation.Conclusions Participants perceived EPAs as strengthening educational accountability and competence assessment without altering legal responsibilities. Successful implementation depends on alignment with local context, emphasizing their role as flexible educational tools rather than legal instruments. Continued research should examine their long-term legal and institutional impact in postgraduate training.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.047 | 0.041 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.009 | 0.009 |
| Scholarly communication | 0.005 | 0.009 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 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".