Delving into the Social Ecology of Leisure-Time Physical Activity Among Adolescents From South Eastern Spain
Bibliographic record
Abstract
BACKGROUND: Worldwide, there is a growing concern with adolescents' low levels of physical activity (PA). We used a comprehensive social ecological framework to uncover factors associated with leisure-time physical activity (LTPA) among adolescents from southeastern Spain. METHODS: A population-based sample of 3249 adolescents aged 12-17 participated in a school-based survey in 2006. Potential correlates of participation in and level of LTPA were assessed through self-report. LTPA levels were also self-reported. We used gender-stratified logistic regression models to examine the associations among the variables of interest. RESULTS: Consistent with a social ecological perspective, analyses revealed several factors, corresponding to different levels of organization (demographic, biological, psychological, behavioral, social) and behavioral settings (family, peer group, school), significantly associated with LTPA. Some of these factors varied as a function of gender and depending on whether the outcome considered was nonparticipation vs. participation in LTPA or high vs. low level of involvement among participants. Overall, the findings highlight the role of health-related participation motives, significant others' attitudes toward PA, and grade in physical education as correlates of LTPA in this sample. CONCLUSIONS: Continued research is necessary to understand the complex interplay of factors and settings associated with adolescent LTPA and the role of gender.
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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 | 0.000 |
| 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 | 0.000 |
| 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".