<scp>Family‐based</scp> physical activity interventions and family functioning: A systematic review
Bibliographic record
Abstract
Family physical activity (PA) can confer multiple health benefits, yet whether PA interventions affect general family functioning has not been appraised. The purpose of this review was to evaluate studies that have examined the effect of family PA interventions, where child PA was the focus of the intervention, on constructs of family functioning. Literature searches were concluded on January 11, 2022 using seven common databases. Eligible studies were in English, utilized a family PA intervention, and assessed a measure of family functioning as a study outcome. The initial search yielded 8413 hits, which was reduced to 20 independent PA interventions of mixed quality after screening for eligibility criteria. There was mixed evidence for whether family PA interventions affected overall family functioning; however, analyses of subdomains indicated that family cohesion is improved by PA interventions when children are in the early school years (aged 5-12). High-quality studies also showed an impact of family PA interventions on family organization. Targeted interventions at specific family subsystems (e.g., father-son, mother-daughter), characteristics (low-income, clinical populations, girls), and broad multibehavioral interventions may have the most reliable effects. Overall, the findings show that family PA interventions can promote family cohesion and organization, particularly among families with children in the early school years. Higher quality research, employing randomized trial designs and targeting specific intervention and sample characteristics (e.g., different clinical conditions, specific parent-child dyads), is recommended in order to better ascertain the effectiveness of these approaches.
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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 | 0.006 | 0.032 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.005 |
| Bibliometrics | 0.011 | 0.015 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.017 | 0.001 |
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".