Psychosocial work stressors, high family responsibilities, and psychological distress among women: A 5‐year prospective study
Bibliographic record
Abstract
BACKGROUND: Psychological distress is a strong and independent predictor of major depression. Assuming multiple roles (such as being both a mother and an employee) under stressful conditions may lead to psychological distress. This study evaluated, for the first time, the longitudinal effect of the simultaneous exposure to psychosocial work stressors and high family responsibilities on women's psychological distress. METHODS: Women were assessed at baseline (N = 1307) and at 3- and 5-year follow-ups. Psychosocial work stressors of the demand-control and effort-reward imbalance models were measured with validated questionnaires. Family responsibilities were also self-reported and referred to the number of children and their age(s) as well as housework and childcare. Psychological distress was measured with the validated Psychiatric Symptoms Index questionnaire. Prevalence ratios (PR) of psychological distress were modeled with log-binomial regressions. RESULTS: Having high family responsibilities did not increase women's prevalence of psychological distress. However, being exposed to either job strain or effort-reward imbalance led to a higher prevalence of psychological distress at the 3- and 5-year follow-ups (PR of 1.25-1.62). Being simultaneous exposed to these psychosocial work stressors and high family responsibilities also increased the prevalence of psychological distress (PR of 1.44-1.87), but no interactions were observed between stressors and responsibilities. CONCLUSIONS: In this 5-year prospective study, simultaneous exposure to psychosocial work stressors and high family responsibilities increased the prevalence of psychological distress among women. Work stressors were, however, driving most of the effect, which reinforces their importance as modifiable risk factors of women's mental health problems.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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 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".