Emotional Exhaustion in Healthcare Workers
Bibliographic record
Abstract
OBJECTIVE: Emotional exhaustion (EE)-the first stage of burnout-is related to preventable work environment exposures. We examined the understudied impact of organizational support for safety (OSS) and safety hazards (SH) on EE in a mixed licensed and unlicensed population of healthcare workers (HCWs). METHODS: A work environment exposures survey was conducted in five US public healthcare facilities in 2018-2019. A total of 1059 questionnaires were collected from a predominantly female population of mixed HCWs. RESULTS: Mean EE scores were higher among women, direct care workers, and younger subjects. In linear regression models, EE was positively associated with SH, emotional labor, psychological demands, physical demands, job strain, assault, and negative acts, while OSS was negatively associated. Safety hazard s both mediated and moderated the relationship between OSS and EE. CONCLUSIONS: When perception of SH is high, OSS has less impact on reducing EE, suggesting a need to effectively put safety policies to practice for improving EE in HCWS.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".