Exploring the Construct of Psychological Safety in Medical Education
Bibliographic record
Abstract
PURPOSE: Psychological safety (PS) is recognized as key in health professions education. However, most studies exploring PS in medical education have focused on mistreatment, thus focusing on what PS is not. The authors set out to explicitly explore learners' concept of PS in the context of medical education to better understand and define PS and its educational consequences for medical students. METHOD: This descriptive exploratory study was conducted in the context of a pilot peer-assisted learning (PAL) program. The program brought together residents and medical students for 16 semiformal learning sessions. Eight medical students from a PAL program were recruited for semistructured interviews to explore their experiences of PS. Transcripts were thematically analyzed using an inductive approach, and social ecological theory was integrated in the later stages of analysis. RESULTS: Students described PS as not feeling judged. Having supportive relationships with peers and mentors improved PS. Students' sense of PS appeared to free them to focus on learning in the present moment without considering the consequences for their image in the eyes of others. Feeling safe also seemed to facilitate relationship building with the mentors. CONCLUSIONS: A sense of PS appears to free learners from constantly being self-conscious about projecting an image of competence. This enables learners to be present in the moment and concentrate on engaging with the learning task at hand. The authors propose that the term "educational safety" be used to describe a relational construct that can capture the essence of what constitutes PS for learners.
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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 | 0.008 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.004 | 0.013 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.007 |
| 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".