Predicting new major depression symptoms from long working hours, psychosocial safety climate and work engagement: a population-based cohort study
Bibliographic record
Abstract
OBJECTIVES: This study sought to assess the association between long working hours, psychosocial safety climate (PSC), work engagement (WE) and new major depression symptoms emerging over the next 12 months. PSC is the work climate supporting workplace psychological health. SETTING: Australian prospective cohort population data from the states of New South Wales, Western Australia and South Australia. PARTICIPANTS: At Time 1, there were 3921 respondents in the sample. Self-employed, casual temporary, unclassified, those with working hours <35 (37% of 2850) and participants with major depression symptoms at Time 1 (6.7% of 1782) were removed. The final sample was a population-based cohort of 1084 full-time Australian employees. PRIMARY AND SECONDARY OUTCOME MEASURES: The planned and measured outcomes were new cases of major depression symptoms. RESULTS: Long working hours were not significantly related to new cases of major depression symptoms; however, when mild cases were removed, the 41-48 and ≥55 long working hour categories were positively related to major depression symptoms. Low PSC was associated with a threefold increase in risk for new major depression symptoms. PSC was not related to long working hours, and long working hours did not mediate the relationship between PSC and new cases of major depression symptoms. The inverse relationship between PSC and major depression symptoms was stronger for males than females. Additional analyses identified that WE was positively related to long working hours. Long working hours (41-48 and ≥55 hours) mediated a positive relationship between WE and major depression symptoms when mild cases of major depression were removed. CONCLUSION: The results suggest that low workplace PSC and potentially long working hours (41-48; ≥55 hours/week) increase the risk of new major depression symptoms. Furthermore, high WE may increase long working hours and subsequent major depression symptoms.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 teacher head, 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".