Shame in medical clerkship: “You just feel like dirt under someone’s shoe”
Bibliographic record
Abstract
INTRODUCTION: This study explores how senior medical students' experience and react to shame during clinical placements by asking them to reflect on (1) manifestations of shame experiences, (2) situations and social interactions that give rise to shame, and (3) perceived effects of shame on learning and professional identity development. METHODS: In this interpretive study, the authors recruited 16 senior medical students from two classes at a Norwegian medical school. In three focus group interviews, participants were invited to reflect on their experiences of shame. The data were analyzed using systematic text condensation, producing rich descriptions about students' shame experiences. RESULTS: All participants had a range of shame experiences, with strong emotional, physical, and cognitive reactions. Shame was triggered by a range of clinician behaviours interpreted as disinterest, disrespect, humiliation, or breaches of professionalism. Shame during clinical training caused loss of confidence and motivation, worries about professional competence, lack of engagement in learning, and distancing from shame-associated specialties. No positive effects of shame were reported. DISCUSSION: Shame reactions in medical students were triggered by clinician behaviour that left students feeling unwanted, rejected, or burdensome, and by humiliating teaching situations. Shame had deleterious effects on motivation, learning, and professional identity development. This study has implications for learners, educators, and clinicians, and it may contribute to increased understanding of the importance of supportive learning environments and supervisors' social skills within the context of medical education.
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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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.007 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".