Entrustable professional activity use in emergency medicine: A scoping review
Bibliographic record
Abstract
Objective: The objective was to scope the literature and describe the extent and type of evidence about entrustable professional activities (EPAs) in postgraduate emergency medicine (EM) education. Methods: Joanna Briggs Institute's methodology was used to find and extract relevant data from documents found in Ovid MEDLINE, EMBASE, and CINAHL, supplemented by a gray literature search using Google Advanced for EPA frameworks. Eligible documents discussed EPAs for doctors in structured EM training programs. Data extracted included research methods, research approach, participants, scope, EPA element addressed, and dominant logic used by EPA creators. Results: Data were extracted from 58 documents. Thirty-four of the documents (58.6%) were peer-reviewed journal articles, 18 (31.1%) were conference abstracts, and six (10.4%) were curriculum documents from EM organizations. Thirty documents were from Canada (51.7%). Twenty-five documents (43.1%) took an explorative approach. Twenty-one documents (36.2%) were translational in approach. Thirteen EPA frameworks, containing a total of 158 EPAs, were found. Conclusions: EM is an expanding area of EPA development, but frameworks remain highly variable and unstandardized. Most studies are explorative or translational, leaving gaps in experimental research to justify EPA adoption and observational research to assess real-world outcomes.
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 | 0.013 | 0.046 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.020 | 0.020 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".