The Association between Role Overload and Women's Mental Health
Bibliographic record
Abstract
OBJECTIVE: To determine the importance of role overload (the extent to which a person feels overwhelmed by her total responsibilities) relative to other known social determinants of women's mental health. METHODS: A Canadian national, random sample, cross-sectional telephone survey in 2003 assessed the association among role overload, types and quality of roles (parent, employee, spouse), sociodemographics, and mental health (using the SF-12) using linear regression. Analysis included 716 women aged 25-54 who indicated that their youngest child living in the household was aged < or =17 years. RESULTS: Perceptions of greater role overload were associated with poorer mental health (p < 0.0001). Women working <35 hours per week (p = 0.04) or 35-40 hours per week (p 5 0.002) reported better mental health than nonemployed women, as did women with the highest annual household income ($70,000+)(p = 0.001). Also associated with better mental health were higher marital status quality scores for both married and single women (p < 0.001), higher job quality scores among employed women (p = 0.02), greater homemaking quality scores among unemployed women (p = 0.03), and women reporting high parental quality (p = 0.04) CONCLUSIONS: Role overload showed a stronger relationship to mental health than other sociodemographic variables, including income. Our findings indicate the importance of measuring women's experience of their multiple roles rather than focusing on single roles. More research is warranted on the totality of women's experiences of their many social role obligations.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".