Overtime work and stress response in a group of Japanese workers
Bibliographic record
Abstract
BACKGROUND: Working long overtime hours is considered a cause of mental health problems among workers but such a relationship has yet to be empirically confirmed. AIM: To clarify the influence of overtime work on response to stress and to assess the role of other stress-related factors on this relationship. METHODS: The study was conducted among 24 685 employees of a company in Japan. Stress response, job stressors and social supports were assessed by the Brief Job Stress Questionnaire. Participants were divided into five categories of overtime (0-19, 20-39, 40-59, >or=60 h of overtime per month and exempted employees). RESULTS: The nonadjusted odds ratios for stress response for 40-59 and >or=60 overtime hours per month in reference to 0-19 overtime hours were 1.11 [95% confidence interval (CI) 1.03-1.19] and 1.62 (95% CI 1.50-1.76), respectively. After adjustment for self-assessed amount of work, mental workload and sleeping time, the association between overtime work and stress response disappeared. CONCLUSIONS: This large cross-sectional study shows that overtime work appears to influence stress response indirectly through other stress factors such as self-assessed amount of work, mental workload and sleeping time.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".