Path analysis of work conditions and work–family spillover as modifiable workplace factors associated with depressive symptomatology
Bibliographic record
Abstract
Abstract Background: Literature pertaining to the relationship between workplace factors and depression has been compartmentalized: work conditions, family conditions, and work–family balance have been studied separately as predictors of depressive symptoms but not concurrently. Objective: Work conditions and work–family spillover were considered concurrently as modifiable workplace factors associated with depressive symptomatology, while controlling for confounding socio‐economic factors. Methods: This cross‐sectional study involved 218 female health care workers who completed a survey assessing work conditions [Effort–Reward Imbalance (ERI) scale and Job Content Questionnaire (JCQ)], work–family balance (work–family spillover scale), sociodemographic information, and depressive symptoms [Center for Epidemiological Studies Depression (CES‐D) scale]. Results: Path analysis supported the presence of a direct relationship between depressive symptoms and high effort–reward imbalance, high negative work–family spillover, low positive family‐to‐work spillover, and low education. The indirect effect of low support from work was mediated by negative work‐to‐family spillover and high effort–reward imbalance. The indirect effect of high effort–reward imbalance was mediated by increased negative work‐to‐family spillover. The indirect effect of having children 18 years or younger was mediated by decreased positive family‐to‐work spillover. An indirect effect of low education was mediated by high effort–reward imbalance and high negative work‐to‐family spillover. Conclusions: The association between work conditions and depressive symptomatology is mediated by increased negative work‐to‐family spillover. The impact of having young children is mediated by decreased positive family‐to‐work spillover. Copyright © 2006 John Wiley & Sons, Ltd.
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 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".