Workplace Causality Orientations Moderate Impostorism and Burnout: New Insights for Wellness Interventions in Graduate Medical Education
Bibliographic record
Abstract
Theory: Impostor phenomenon (IP) is strongly linked to physician burnout, but the nature of this association is not well understood. A better grasp of the mechanism between these constructs could shed new light on ways to mitigate physician IP and burnout. Grounded in self-determination theory (SDT), the present study explores whether and how residents’ general causality orientations at work—impersonal, controlled, and autonomous—each moderate the effect of IP on physician burnout. Hypotheses: We theorized that the autonomous orientation would buffer the facilitative effect of IP on burnout, while the controlled and impersonal orientations would each enhance it to varying degrees. Method: Two hundred forty-three residents from the Universities of Saskatchewan, Calgary, and Alberta, across various programs, specialties, and years of training, completed a survey containing demographic questions and three previously validated instruments: the Clance Impostor Phenomenon Scale, Causality Orientations at Work Scale, and Oldenburg Burnout Inventory. We used partial correlation analyses to test our moderation hypotheses. Results: In line with what we expected, the autonomous causality orientation buffered the facilitative effect of IP on burnout, while the controlled and impersonal causality orientations each enhanced it. Conclusions: Results suggest that possessing a stronger autonomous causality orientation (and creating learning/work environments that prime it) will dampen the effect of IP on burnout, while possessing a stronger controlled or impersonal causality orientation (and creating learning/work environments that prime them) will each augment it. Findings and their implications are discussed in terms of instigating theory-informed, system-level wellness interventions in graduate medical education.
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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 | 0.005 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.004 |
| 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".