The Moderating Role of Employees’ Humor Styles on the Relationship between Job Stress and Emotional Exhaustion
Bibliographic record
Abstract
In today’s work conditions, job stress and emotional exhaustion are serious threats for the health of employees. Previous research suggests a relationship between job stress and emotional exhaustion. The way individuals use humor has been associated with different coping strategies. The aim of this study is to investigate the moderating role of employees’ humor styles on the relationship between job stress and emotional exhaustion. 116 participants completed self-reported measures assessing their job stress, emotional exhaustion and humor styles. For data analyses a series of hierarchical moderated regression analyses were conducted. The findings show that self-enhancing and self-defeating humor styles have moderating effects on the relationship between job stress and emotional exhaustion. As the level of self-enhancing humor increases, the effect of job stress on emotional exhaustion is attenuated, on the other hand, as the level of self-defeating humor increases, the effect of job stress on emotional exhaustion is intensified. Findings regarding the effects of employees’ humor styles are discussed.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 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".