Childrens?? Physical Activity Places
Bibliographic record
Abstract
Growing empirical evidence documents built environment effects on adults' physical activity, but little is known about environment effects on children's physical activity. Indeed, environments in which adults are active may differ significantly from the environments in which children are active, necessitating a sophisticated approach to public health and environment approaches to increase physical activity across the lifespan. Purpose To examine the relations between the number of places children are active and their levels of physical activity, neighborhood environment, and individual characteristics. Methods Parents of 201 children 4–18 years old were recruited from high and low walkable neighborhoods in King County, WA. Parents reported on the places where their children are active and the places' convenience to their home, their children's activity level, and individual characteristics. Results From a list of 15 potential places in which children could be active in a typical month, friends' homes, own yards, parks, and playgrounds were more frequently visited by children in order to be active than the street and gyms or other paid facilities. The number of places children went to be active was positively related to the number of activity-related facilities convenient to home (<10 minute walk from home) (p<.019), but the number of different children's activity places decreased with child age (p<.007). The number of places a child went to be active was positively related to their level of physical activity (p<.001). In contrast, children went to fewer places to be active when living in neighborhoods marked by environmental factors associated with higher adult physical activity, particularly adults walking for transport (e.g., higher residential density, higher land use mix) (p<.04). Conclusions Children's physical activity appears to benefit from a greater variety of places in which to be active and greater convenience of such activity places. However, the built environment in which adults are more active in the form of walking for transport may not necessarily translate into increased variety in the places in which children are active. Further evaluation of physical activity environments and the potential unique impact of such environments on children is warranted. Supported by NIH grant HL67350.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.052 | 0.008 |
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".