A descriptive study of the timing and type of physical activity that is being resumed in early postpartum
Bibliographic record
Abstract
Postpartum physical activity (PA) is an important component of the woman's health. Recently, more attention has been paid to develop guidance for safe return to PA after delivery, including return to running. Little is known about when women start PA after delivery and what type of PA they are practicing. The objectives were to (1) describe early postpartum PA (≤6 weeks), (2) compare women's characteristics between those who started any kind of PA and those who did not, and those who started and did not start running, and (3) explore predictors of PA and running. Ninety-one women, who were part of a longitudinal cohort study, were included. At 6 weeks postpartum, PA was assessed using a questionnaire. Predictors of PA and running were age, education, parity, pre-pregnancy body mass index, prenatal PA, gestational weight gain, prematurity, delivery mode, season, and breastfeeding. The Wilcoxon rank-sum test, Fischer's exact test, and logistic regression analyses were used. Eighty-five women (93%) resumed PA by 6 weeks postpartum. Walking was practiced by 92% of women for 127.0 ± 81.3 min/week. Running was the second most popular activity, practiced by 11% of women for 57.5 ± 31.8 min/week. Walking and running were started around 2.0 and 3.6 weeks after delivery, respectively. Women who delivered in spring or summer were more likely to resume PA by 6 weeks postpartum, and those who ran while pregnant had five-fold higher odds of starting to run by 6 weeks postpartum (OR:5.03, 95%CI 1.27; 19.92). These findings improve our understanding of PA practice, including running, in early postpartum.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".