Health-Promoting Behaviors Through Pregnancy, Maternity Leave, and Return to Work: Effects of Role Spillover and Other Correlates
Bibliographic record
Abstract
Women's health-promoting behavior changes and their correlates across the transition to motherhood and return to work are insufficiently understood. The purpose of this study was to describe and compare women's health-promoting behaviors, particularly physical activity (PA), across these transitions. A prospective, observational design was employed to assess 243 female healthcare workers from 3 sites with regard to health-promoting behaviors, and their demographic (e.g., age, parity) and psychosocial (i.e., work-family role spillover) correlates. Forty-two participants were recruited while pregnant and re-assessed during maternity leave and upon return to work, and compared to 201 non-pregnant participants. No significant changes in health-promoting behaviors were observed from pregnancy through the postpartum. Pregnant participants reported better nutrition than comparison participants (p=.001), and were more likely to check their pulse when exercising (p=.004). During pregnancy, health-promoting behaviors were related to parental status, with first-time mothers engaging in more positive behaviors. Correlates of PA during maternity leave and return to work included family income and exercise history. Positive family-to-work spillover was significantly greater among pregnant women than among comparison participants (p<.001), and positive work-to-family spillover was related to greater PA upon return to work (p<.01). This study reveals little variability in health-promoting behaviors from the prenatal to the postpartum period. Both demographic and psychosocial factors have effects on health-promoting behaviors, and we must look to these correlates to promote increased PA.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".