Examining enablers and barriers to entrustable professional activity acquisition using the theoretical domains framework: A qualitative framework analysis study
Bibliographic record
Abstract
Background: Without a clear understanding of the factors contributing to the effective acquisition of high-quality entrustable professional activity (EPA) assessments, trainees, supervising faculty, and training programs may lack appropriate strategies for successful EPA implementation and utilization. The purpose of this study was to identify barriers and facilitators to acquiring high-quality EPA assessments in Canadian emergency medicine (EM) training programs. Methods: We conducted a qualitative framework analysis study utilizing the Theoretical Domains Framework (TDF). Semistructured interviews of EM resident and faculty participants underwent audio recording, deidentification, and line-by-line coding by two authors, being coded to extract themes and subthemes across the domains of the TDF. Results: From 14 interviews (eight faculty and six residents) we identified, within the 14 TDF domains, major themes and subthemes for barriers and facilitators to EPA acquisition for both faculty and residents. The two most cited domains (and their frequencies) among residents and faculty were environmental context and resources (56) and behavioral regulation (48). Example strategies to improving EPA acquisition include orienting residents to the competency-based medical education (CBME) paradigm, recalibrating expectations relating to "low ratings" on EPAs, engaging in continuous faculty development to ensure familiarity and fluency with EPAs, and implementing longitudinal coaching programs between residents and faculty to encourage repetitive longitudinal interactions and high-quality specific feedback. Conclusions: We identified key strategies to support residents, faculty, programs, and institutions in overcoming barriers and improving EPA assessment processes. This is an important step toward ensuring the successful implementation of CBME and the effective operationalization of EPAs within EM training programs.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".