Parenting Practice and Physical Activity: Exploring the Gendered Influences of Modeling, Support, and Control on Young Children's Objectively Measured Physical Activity
Bibliographic record
Abstract
This study examined associations between parents’ physical activity-related parenting practices and objectively measured activity levels in their preschool-aged children. Survey data from 16 mother-father dyads participating in the Guelph Family Health Study was used to generate estimates of maternal and paternal physical activity, modeling, supportive, and controlling behaviours. Physical activity (PA) in the 24 participating children (15 males, 9 females) was measured using accelerometers. Linear regression modeling using the generalized estimating equation (GEE) approach was applied to identify associations between parenting practices and children’s moderate-to-vigorous and total physical activity (MVPA and TPA). Analyses stratified by child sex found positive associations between modeling by either parent and female children’s MVPA and TPA, while paternal enrolment of children in structured activities and maternal control were positively associated with MVPA and TPA among males. While maternal control facilitated activity among males, it displayed a significant negative association with female children’s activity levels. Our results revealed differing responses by male and female children to mothers’ and fathers’ PA parenting practices, and suggest the need for further research into the ways that maternal and paternal modeling, support, and control influence young children’s PA behaviours across sexes.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".