Sex-specific interaction effects of age, occupational status, and workplace stress on psychiatric symptoms and allostatic load among healthy Montreal workers
Bibliographic record
Abstract
Socio-demographics and workplace stress may affect men and women differently. The aim of this cross-sectional study was to assess sex-specific interactions among age, occupational status, and workplace Demand-Control-Support (D-C-S) factors in relation to psychiatric symptoms and allostatic load levels representing multi-systemic "wear and tear". It was hypothesized that beyond main effects, D-C-S factors would be moderated by occupational status and age in sex-specific directions predictive of subjective psychiatric symptoms and objective physiological dysregulations. Participants included healthy male (n = 81) and female (n = 118) Montreal workers aged 20 to 64 years (Men: M = 39.4 years, SD = 11.3; Women: M = 42.8 years, SD = 11.38). The Job Content Questionnaire was administered to assess workplace D-C-S factors that included psychological demands, decisional latitude, and social support. Occupational status was coded using the Nam--Powers--Boyd system derived from the Canadian census. Psychiatric symptoms were assessed using the Beck Anxiety Scale and the Beck Depression Inventory II. Sex-specific allostatic load indices were calculated based on fifteen biomarkers. Regression analyses revealed that higher social support was associated with less depressive symptoms in middle aged (p = 0.033) and older men (p = 0.027). Higher occupational status was associated with higher allostatic load levels for men (p = 0.035), while the reverse occurred for women (p = 0.048). Women with lower occupational status but with higher decision latitude had lower allostatic load levels, as did middle-aged (p = 0.031) and older women (p = 0.003) with higher psychological demands. In summary, age and occupational status moderated workplace stress in sex-specific ways that have occupational health implications.
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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 | 0.000 | 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".