Exploring Moderators of the Relationship between Physical Activity Behaviors and Television Viewing in Elementary School Children
Bibliographic record
Abstract
PURPOSE: Previous research suggests that there is limited evidence to support a negative association between physical activity (PA) behaviors and television (TV) viewing time in children. The purpose of this study was to extend the research involving PA-TV viewing relationships and to explore potential moderators, including gender, ethnicity, weekday/ weekend behaviors, structured/unstructured activities, and seasonal variability. DESIGN: A 9-month longitudinal design, across one school year, with assessments every 3 months. SETTING: Elementary schools in the Vancouver and Richmond districts of British Columbia, Canada. Subjects. Subjects (N = 344; 47% female) were 9- to 11-year-old children who participated in a school-based PA initiative from September 2003 to June 2004. INTERVENTION: Not applicable. MEASURES: Assessments of PA were measured using the Physical Activity Questionnaire for Children. TV viewing time and structured PA were measured using a self-report questionnaire. ANALYSIS: Basic descriptives, Pearson r bivariate correlations and moderated multiple regressions with mean centered variables. RESULTS: No significant interaction effects were found for any of the proposed moderators. Null bivariate correlations are supportive of findings in previous literature. CONCLUSIONS: Our results did not find support for PA-TV viewing relations, regardless of gender, ethnicity, structured PA, and seasonal variability. PA interventions aimed at modifying sedentary behaviors, such as TV viewing, may not be warranted.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".