The role of social support in predicting physical activity and wellbeing within the first year of giving birth
Bibliographic record
Abstract
Many new moms express a desire to be physically active but encounter a variety of barriers, the most common being lack of perceived social support. Different types of support might be needed for new mother to be active (e.g., for exercise- or postpartum-related barriers).While social support (SS) has been shown to improve physical activity and well-being, there is a need to understand moderators of these relationships. Exercise-related cognitive errors (ECEs) bias how accurately individuals view their physical activity and might impact the support-activity relationship. It was hypothesized that ECEs and SS would interact to predict physical activity and psychological wellbeing in the first year after giving birth. New moms (N= 268, Mage=29.96) completed a self-reported survey using the ECE questionnaire (ECE-Q), Social Support for Exercise scale (SSES; subscale Family), a modified Postpartum Support questionnaire (PSSQ; Subscale Family), and Psychological Wellbeing scale (PWBS), and moderate-to-vigorous physical activity (MVPA). SSES (B= .258, p < .001) and the ECE-Q (B= .130, p= .036) predicted MVPA (R2=.07, p < .001) beyond covariates. SSES (B= -. 146, p=.023), PSSQ (B= .461, p
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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 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".