Feeling the Pulse: An Exploration of the Emotional Effects of Competency-Based Medical Education in Psychiatry
Bibliographic record
Abstract
Introduction: Competency-based medical education (CBME) is a learner-centered outcomes-based approach. Competence by Design (CBD) is a hybrid time-based and outcomes-based CBME model that was adopted by all Royal College of Physicians and Surgeons of Canada-based residency training programs, with the primary objective of enhancing postgraduate medical education quality. However, preliminary findings suggest that residents experience higher levels of stress, anxiety, and exhaustion in CBD than with previous curricula. This thesis aims to identify and understand the emotional effects of CBME on residents, faculty, and administrative staff. Methods: This study used a qualitative approach, specifically hermeneutic phenomenology. Seven residents, six faculty members (several with education leadership roles), and one administrative staff member from a postgraduate Psychiatry program were recruited. Participants underwent semi-structured, one-on-one interviews where they were probed on their emotions with CBME. Interviews were transcribed and analyzed using a line-by-line approach that generated individual meaning units and, subsequently, themes. Results: Five themes were identified: 1) Education is an emotional experience; 2) The emotional toll of CBD; 3) CBD is a failed educational promise—Expectations vs. realities; 4) Structural and administrative burdens of CBD; and 5) Survival of educational demands—The quest for coping. Participants initially struggled to articulate their emotions, but expressed surprise at realizing they did have strong, often negative, emotions related to CBD. There was also a dissonance identified between the anticipated benefits and the execution of CBD. Furthermore, participants highlighted administrative and structural challenges of CBD, specifically regarding Entrustable Professional Activities, which were a burden and lacked much educational value. Participants discussed using various coping strategies to manage CBD’s demands. Conclusion: The findings of this work suggest that CBD has a negative emotional impact on residents and faculty, specifically due to tension between CBD’s theoretical benefits and its practical challenges, including increased emotional burden and structural challenges.
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.008 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.003 |
| 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".