High School Sport Participation: Does It Have an Impact on the Physical Activity Self-efficacy of Adolescent Males?
Bibliographic record
Abstract
Physical inactivity continues to be a major concern in the lives of youth. It is possible that participation in high school sport might contribute to enhancing self-efficacy which, in turn, would positively influence physical activity levels. In this study, the association between physical activity participation and self-efficacy for physical activity was measured in adolescent males from a private high school in Canada. Also, the possibility that self-efficacy levels differed between school sport participants and non-school sport participants was explored. The results of the Spearman's p test showed a moderate positive, and significant correlation between the Physical Activity Questionnaire for Adolescents (PAQ-A) and the Self-Efficacy for Daily Physical Activity Questionnaire (SEPAQ) scores, r(113) = .571, p < .01. The multiple regression analysis showed that PAQ-A score significantly predicted SEPAQ scores, b = 10.95, t(113) = 6.63, p < .001. However, school sport participation did not significantly predict SEPAQ scores, b = 0.99, t(113) = 0.97, p > .05. Interestingly, PAQ-A scores and school sport participation explained a significant proportion of variance in SEPAQ scores, R^2= 0.33, F (2, 112) = 27.11, p < .001. Results from this study support previous research regarding the positive connection between physical activity and self-efficacy. These results also suggest that small increases in physical activity, whether through school sport or physical education, may influence not only physical health but psychological health for youth. Implications for male participation in physical activity are discussed along with ideas for increasing self-efficacy within the physical education context.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".