Perceptions of High-Involvement Work Practices, Person-Organization Fit, and Burnout: A Time-Lagged Study of Health Care Employees
Bibliographic record
Abstract
Previous research demonstrates that high-involvement work practices (HIWPs) may be associated with burnout (emotional exhaustion and depersonalization); however, to date, the process through which HIWPs influence burnout is not clear. This article examined the impact of HIWPs on long-term burnout (emotional exhaustion and depersonalization) by considering the mediating role of person-organization fit (P-O fit) in this relationship. The study used a time-lagged design and was conducted in a Canadian general hospital among health care personnel. Findings from structural equation modeling (N = 185) revealed that perceived HIWPs were positively associated with P-O fit. There was no direct effect of HIWPs on burnout; rather, P-O fit fully mediated the relationship between employee perceptions of HIWPs and burnout. This study fills a void in the HR and burnout literature by demonstrating the role that P-O fit has in explaining how HIWPs alleviate emotional exhaustion and depersonalization. © 2016 Wiley Periodicals, Inc.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".