Relationship Between Body Composition and Physical Literacy in Chilean Children (10 to 16 Years): An Assessment Using CAPL-2
Bibliographic record
Abstract
Objectives: The aim of this study was to evaluate the levels of physical literacy (PL) in school children (10 to 16 years) in Santiago, Chile, and to explore the relationship between PL and body mass index (BMI). In addition, gender and age differences were analyzed in relation to PL levels in a context where childhood obesity remains a public health challenge. Methods: A total of 439 students in grades 5–8 were assessed using the Canadian Assessment of Physical Literacy-2 (CAPL-2) questionnaire. Demographic variables (sex, age, and BMI) were correlated with levels of motivation to engage in physical activity and physical activity knowledge. Chi-square and effect size were applied. Results: The results revealed a significant correlation between motivation for physical activity and gender, with boys showing higher levels of motivation than girls (χ² = 12.403, p < 0.006). In addition, an inverse relationship was observed between BMI and motivation (effect size = 0.198), suggesting that more motivated children tend to have a healthier BMI. Knowledge about physical activity increased with age (χ² = 60.460, p < 0.001) but did not have a significant influence on BMI. Conclusions: The findings highlight the need to design gender-specific interventions that enhance motivation as a key factor in promoting a healthy lifestyle and physical activity adherence. Public health strategies should include motivation-driven approaches to foster physical literacy and long-term engagement in physical activity, particularly for girls, to address pediatric health challenges in Chile. Public health policies should address these factors to improve pediatric health outcomes.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".