Partners’ overwork and individuals’ wellbeing and experienced relationship quality
Bibliographic record
Abstract
The negative impact of long work hours, or overwork, on individuals' physical and psychological wellbeing is well documented. Less is known about the impact of overwork on individuals' families, especially in regard to partners. In this paper, we address this gap in the literature using high quality data from the Work, Family, and Health Network in a sample of IT workers in the US (N=590). Specifically we examine whether partners' long work hours are associated with individuals' perceived stress, time adequacy with partner, and relationship quality, and whether these relationships vary by gender. In addition, following the marital stress model, we investigate whether any negative correlation between partners' long work hours and relationship quality is mediated by time adequacy or perceived stress. We find that women partnered to men who work long hours (50 or more hours per week) have significantly higher perceived stress and significantly lower time adequacy and relationship quality compared to women partnered to men who work a standard full-time work week (35-49 hours). Further, the increased stress associated with being partnered to a man who overworks, not lower time adequacy, mediates the negative relationship between overwork and relationship quality. Conversely, we find that men partnered to women who work long hours report no differences in stress, time adequacy, or relationship quality than men who are partnered to women who work a standard full-time work week. Our results highlight the need for more research that examines the impact of overwork on individuals and their families.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".