Life and Work-life Balance Satisfaction Among Parents Working From Home: the Role of Work-time and Childcare Demands
Bibliographic record
Abstract
Abstract This study examines the relationship between working from home (WFH) and satisfaction with work-life balance (WLB) and life satisfaction among parents with dependent children, focusing on moderating factors related to work hours and childcare demands. We differentiate between parents who continued WFH from before the COVID-19 pandemic and those who began WFH during the pandemic. Using a dataset collected via a representative online survey in Canada, Germany, Italy, Poland, Sweden, and the United States, we provide cross-national estimates of WFH’s impact on WLB and life satisfaction. Data collection took place between June and September 2021, capturing a unique period when WFH was widespread but pandemic-related restrictions had been lifted. Our findings show that both fathers and mothers across all countries reported higher WLB when WFH, particularly if they gained the opportunity to WFH during the pandemic. However, the association between WFH and life satisfaction was less consistent and varied by gender and country. For parents who worked from home prior to the pandemic, WFH was linked to higher WLB satisfaction only if they did not work long hours. Interestingly, mothers who began WFH during the pandemic reported higher WLB satisfaction even when working long hours or bearing primary childcare responsibilities. This suggests that the newly gained ability to WFH was especially valued by mothers as a vital means of balancing intensive work and family demands during the pandemic. These findings underscore the importance of distinguishing between the short- and long-term effects of WFH on WLB in 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 | 0.001 | 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 | 0.001 | 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) | 0.004 | 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".