A Longitudinal Study of the Effect of Organized Physical Activity on Free Active Play
Bibliographic record
Abstract
PURPOSE: The relationship between organized sport participation and positive youth development is well established. However, overinvolvement in sport and organized physical activity has been identified as having a potentially negative effect. Overscheduling and its impact on free play is one concern, given the importance of free play to overall health and development. Currently, it is not known if greater participation in organized sport has a positive or negative effect on discretionary free play in children and youth. METHODS: The Physical Health and Activity Study Team study was a 5-yr, longitudinal cohort study that followed 2278 fourth grade children (ages 9-10 yr). Organized sport and free play was assessed in the fall of each school year from fifth to eighth grades using self-report questionnaires. RESULTS: Using mixed-effects modeling, we found that higher participation in organized sport was associated with increased participation in free play over time (coefficient = 0.20, P < 0.001). Although this effect was independent of age and socioeconomic status, we did find that boys with high levels of organized participation reported the highest levels of free play overall. CONCLUSIONS: Possible explanations for this association are related to the role sport might play in supporting physical literacy and the development of fundamental movement skills, allowing children to participate in more active free play pursuits. It might also be the case that active children simply seek out both organized and unorganized physical activity opportunities during this developmental period. Limitations and implications for further research and policy are discussed.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".