Encouraging New Moms to Move More—Are We Missing the Mark? A Systematic Review With Meta-Analysis of the Effect of Exercise Interventions on Postpartum Physical Activity Levels and Cardiorespiratory Fitness
Bibliographic record
Abstract
OBJECTIVE: To determine if current exercise interventions were effective at improving physical activity (PA) levels and/or cardiorespiratory fitness (CRF) in postpartum women. DESIGN: Intervention systematic review with meta-analysis. LITERATURE SEARCH: CINAHL, Embase, Medline, PsycINFO, and SPORTDiscus were searched from inception to March 2024. STUDY SELECTION CRITERIA: Participants: postpartum women; intervention: exercise; control: standard care; outcomes: PA levels and/or CRF. DATA SYNTHESIS: Random effects meta-analysis using standardized mean differences (SMDs). Risk of bias was assessed using the Cochrane Risk of Bias 2 (RoB 2) and Risk of Bias in Non-Randomized Studies – Intervention (ROBINS-I). RESULTS: A total of 6041 studies were screened, and 29 were eligible for inclusion. Nineteen studies with adequate control data included outcomes related to PA levels (n = 12) or CRF (n = 7) and were pooled in meta-analyses. There was a small to moderate improvement in CRF (SMD, 0.65; 95% CI [confidence interval]: 0.20, 1.10; I2 = 61%). There was no improvement in PA levels (SMD, −0.13; 95% CI: −0.53, 0.26; I2 = 90%). Frequency, intensity, type, and time of the exercise interventions varied. Twenty-three studies were at high or serious risk of bias. CONCLUSIONS: Postpartum exercise interventions may improve CRF but have an unclear effect on PA levels. Despite numerous exercise interventions to improve health outcomes postpartum, parameters were inconsistent. J Orthop Sports Phys Ther 2024;54(11):687-701. Epub 9 October 2024. doi:10.2519/jospt.2024.12666
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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 | 0.031 | 0.078 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.024 | 0.036 |
| Bibliometrics | 0.007 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.004 | 0.003 |
| 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".