Identifying Factors Associated with Regular Physical Activity in Leisure Time among Canadian Adolescents
Bibliographic record
Abstract
PURPOSE: The purpose of this study was to identify the factors explaining regular physical activity among Canadian adolescents. DESIGN: A cohort study conducted over a period of 2 years. SETTING: A French-language high school located near Québec City. SUBJECTS: A cohort of 740 students (352 girls; 388 boys) aged 13.3 +/- 1.0 years at baseline. MEASURES: Psychosocial, life context, profile, and sociodemographic variables were assessed at baseline and 1 and 2 years after baseline. Exercising almost every day during leisure time at each measurement time was the dependent variable. RESULTS: The Generalized Estimating Equations (GEE) analysis indicated that exercising almost every day was significantly associated with a high intention to exercise (odds ratio [OR]: 8.33, confidence interval [CI] 95%: 5.26, 13.18), being satisfied with the activity practiced (OR: 2.07, CI 95%: 1.27, 3.38), perceived descriptive norm (OR: 1.82, CI 95%: 1.41, 2.35), being a boy (OR: 1.83, CI 95%: 1.37, 2.46), practicing "competitive" activities (OR: 1.80, CI 95%: 1.37, 2.36), eating a healthy breakfast (OR: 1.68, CI 95%: 1.09, 2.60), and normative beliefs (OR: 1.48, CI 95%: 1.14, 1.90). Specific GEE analysis for gender indicated slight but significant differences. CONCLUSIONS: This study provides evidence for the need to design interventions that are gender specific and that focus on increasing intention to exercise regularly.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".