Parental correlates in child and adolescent physical activity: a meta-analysis
Bibliographic record
Abstract
OBJECTIVE: Physical activity (PA) has a profound impact on health and development in children. Parental behaviors (i.e., modeling and support) represent an obvious important factor in child PA. The purpose of this paper was to provide a comprehensive meta-analysis that overcomes the limitations of prior narrative reviews and quantitative reviews with small samples. METHODS: Ten major databases were used in the literature search. One-hundred and fifteen studies passed the eligibility criteria. Both fixed and random effects models with correction for sampling and measurement error were examined in the analysis. Moderator analyses investigating the effects of child's developmental age, study design, parental gender, measurement of child PA, and quality rating were performed. RESULTS: Based on the random effects model, the results showed that parental modeling was weakly associated with child PA (summary r = .16, 95% CI .09-.24) and none of the proposed moderators were significant. Separate analyses examining the moderating effects of parental gender and boys' PA found that that father-son PA modeling (r = .29, 95% CI .21-.36) was significantly higher compared to mother-son PA (r = .19, 95% CI .14-.23; p < .05). However, parental gender did not moderate the relationship between parental modeling and girls' PA (p > .05). The random effects model indicated an overall moderate effect size for the parental support and child PA relationship (summary r = .38, 95% CI .30-.46). Here, the only significant moderating variable was the measurement of child PA (objective: r = .20, 95% CI .13-.26; reported: r = .46, 95% CI .37-.55; p < .01). CONCLUSIONS: Parental support and modeling relate to child PA, yet our results revealed a significant degree of heterogeneity among the studies that could not be explained well by our proposed moderators.
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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 | 0.014 | 0.032 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.016 | 0.046 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".