The Associations Between Job Strain, Workplace PERMA Profiler, and Work Engagement
Bibliographic record
Abstract
OBJECTIVE: Our purpose was to examine the relationship between job strain, work engagement, and the dimensions of well-being according to the workplace PERMA (Positive Emotion, Engagement, Relationships, Meaning, Accomplishment) model. METHODS: Three hundred ten workers completed a web-based questionnaire, namely, the Brief Job Stress Questionnaire, Utrecht Work Engagement scale, and the workplace PERMA profiler. Regression analyses were conducted on well-being and each scale of job strain, including job demands, job control, supervisor support, and coworker support. RESULTS: Job control, supervisor support, and coworker support were significantly correlated with the scores of five dimensions, and happiness of the PERMA profiler (except for between supervisor support and Accomplishment). Job demands was only significantly correlated with Engagement and Meaning. CONCLUSIONS: All well-being dimensions were commonly influenced by job control and workplace support, while Engagement and Meaning were also facilitated by challenging job demands.
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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 | 0.000 | 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".