An examination of factors associated with physical activity among youth in Prince Edward Island
Bibliographic record
Abstract
Background: The youth population of Prince Edward Island (PEI) is one of the least active in all of Canada (Colley et al., 2012). The social factors that influence youth physical activity (PA) behaviours are not well understood. There is a body of evidence which suggests there is a relationship between social influences and higher levels of PA; however little is known about the specific influential factors themselves. The purpose of this study was to identify if social factor variables selected based on the Social Cognitive Theory (SCT) and applied post-hoc, were associated with PA as defined by the 2010 CPAGL, in grades 5 to 12, and whether the resulting behaviour was affected by school level and gender (Janssen & LeBlanc, 2010). Methods: The study consisted of secondary data analysis of the Physical Activity Module of the School Health Action, Planning, and Evaluation System (SHAPES) PEI project, which collected self-report data from 4833 students in 58 schools across PEI. Logistic regression analysis was used to examine the variance between gender and within school level, as well as the strength of the association between social factors on youth PA. Results: There was a significant relationship between students meeting the 2010 CPAGL and the number of peers who were physically active. Students’ level of self-efficacy was significantly associated with meeting the 2010 CPAGL, as was students’ overall perceptions of the relationship between academic performance and participation in PA; additionally, male students were found to be significantly more likely to meet the 2010 CPAGL. Conclusion: The findings support the social cognitive concept that peer influence impacts PA behaviour. The findings also support the importance of self-efficacy to youth being engaged in PA. A more comprehensive understanding of the relationship between the school policies and youth behaviour may assist in the development of effective interventions to support increased levels of PA.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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".