Household Income and Psychological Distress: Exploring Women’s Paid and Unpaid Work as Mediators
Bibliographic record
Abstract
Research suggests that a socioeconomic gradient in employed adults' mental health may be partially mediated by their work conditions. Largely ignored in this body of research is the potential role of unpaid domestic labor. The objectives of this paper were to determine whether socioeconomic disparities in mental health were present in a sample of employed, partnered mothers, and if so, identify the intervening mechanisms which contributed to the disparity. Participants for this cross-sectional study were 512 women recruited from an online research panel of residents living in Saskatchewan, Canada. Household income was the primary exposure and psychological distress was the dependent variable. Potential mediators included material deprivation, job control, job demands, work-family conflict, and the conditions of domestic labor. Descriptive analyses followed by simple and multiple mediation analyses were performed. Lower income was associated with greater distress, with material deprivation, work-family conflict, and inequity in responsibility for domestic work acting as mediators. These results suggest that in addition to more well-established mechanisms, the conditions of unpaid domestic labor, particularly how that labor is shared within households, may play a role in the genesis of mental health inequities among employed partnered mothers. Limitations of the study are discussed as are implications for future research.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".