Social support for exercise from pregnancy to postpartum and the potential impact of a mobile application: A randomized control pilot trial in Southern United States
Bibliographic record
Abstract
This study compared perceived social support among women of all body mass index (BMI) categories with an attempt to assess the efficacy of the BumptUp® mobile application to improve social support for exercise during pregnancy and postpartum. Thirty-five pregnant women living in Southern United States were included in the sample. The intervention group received access to the BumptUp® mobile application that was designed to promote physical activity during pregnancy and postpartum. The control group received an evidence-based educational brochure. Perceived social support for exercise was assessed at four-time points using the social support and exercise survey. Outcomes were evaluated at 23-25, 35-37 gestational weeks, and 6 and 12 weeks postpartum. Based on their pre-pregnancy weight and height, BMI was computed to categorize participants into lean, overweight, and obese groups. Social support across BMI categories and between control and intervention groups were compared using linear mixed-effect models. Women grouped in the overweight and obese BMI categories reported receiving significantly lower levels of social support for exercise than women in the lean category throughout pregnancy and postpartum during mid-pregnancy, late pregnancy, and at 12 weeks postpartum (p < 0.05). Although the intervention group received higher social support than the control group throughout all four assessment points, the difference was not statistically significant (p > 0.05). Women with a pre-pregnancy BMI of overweight and obese received lower social support for exercise during pregnancy and postpartum. The efficacy of BumptUp® to improve perceived social support for exercise in pregnancy and postpartum was not evident in the results.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".