The role of daily mindfulness on work–home conflict: a daily study of women leaders
Bibliographic record
Abstract
Purpose We investigate how mindfulness can help women leaders manage the work–home conflict using boundary theory. In this daily diary study, we examine daily levels of mindfulness as an antecedent to daily self-control and perceptions of work–home conflict. We propose that higher levels of daily mindfulness act as a personal resource that fosters self-control capacity, and this leads to a greater ability to manage work–home conflict. Design/methodology/approach A total of 86 women enrolled in a 30-day online mindfulness training program and completed daily surveys after each daily mindfulness training session. Data was analysed using the multilevel structural equation modelling. Findings Results demonstrate that higher levels of daily mindfulness predict lower levels of daily work–home interference, and this relationship is mediated by self-control. This research supports the role of mindfulness through self-control on work–home conflict for women in leadership. Given the relatively high workforce participation among women with caregiving responsibilities, identifying resources that can be cultivated in order to enable more women to stay engaged in the workforce shows promise. Originality/value This study adds to the nascent literature of gendered mental health and well-being in leadership. Notably, women leaders often play a supportive role for employees and co-workers. Our findings suggest mindfulness training can be a useful tool to increase self-control resources in times of crises to mitigate the work–home conflict.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".