Workplace risks and stressors as predictors of burnout: The moderating impact of job control and team efficacy
Bibliographic record
Abstract
Abstract Air medical healthcare (AMH) professionals care for critically‐ill individuals while conveying them to healthcare centres from distant, and frequently dangerous, locations. AMH professionals experience additional health and safety issues beyond the “typical” stressors faced by other healthcare professionals. Therefore, we integrated the safety and psychosocial health literatures to examine the relationship between workplace stressors (risk perception, worries, and patient‐care barriers) and two components of burnout (emotional exhaustion; depersonalization), and the moderating impact of job control and team efficacy for 106 Canadian AMH professionals. Worries over medical hassles and barriers to patient care uniquely predicted emotional exhaustion. Lack of perceived control over one's job was related to exhaustion and depersonalization after controlling for stressors. Job control and team efficacy buffered some of the stressor‐burnout relationships. Copyright © 2009 ASAC. Published by John Wiley & Sons, Ltd.
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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 | 0.002 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".