Lessons Learned from Tobacco Control: A Multilevel Analysis of School Characteristics and Adolescent Physical Activity
Bibliographic record
Abstract
Background: The high prevalence of physical inactivity among children and adolescents (youth) and the associated negative health consequences make it critical to increase physical activity levels. Social-ecological models suggest that the school environment may influence youth health behaviour. However, few studies have examined the school environment in relation to youth physical activity. Purpose: To 1) examine between-school variability in student physical activity, 2) identify school characteristics that account for between-school variability in student physical activity, and 3) examine the association between senior student participation rates in school physical activities and junior student physical activity. Methods: The study consisted of secondary data analysis of the School Health Action, Planning and Evaluation System (SHAPES) Ontario project, which collected self-report data from 69,511 students in 76 secondary schools from seven public health unit districts in Ontario. Multilevel modeling was used to examine between-school variability in student physical activity, as well as school characteristics associated with physical activity. Results: There was significant between-school variability in student physical activity, and the relationship between physical activity and age and gender, respectively. School rates of physical education participation were associated with student physical activity levels. Senior student participation in other physical activities at school, such as playing outside, was associated with junior student physical activity levels. Conclusions: These findings support the social-ecological notion that the school environment can influence adolescent physical activity behaviour. A better understanding of the relationship between the school environment and physical activity will assist in the development of effective school-based policies, programs and interventions to increase physical activity.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.008 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.007 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| 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".