Is There a Meaningful Association Between Physical Literacy and Health Literacy? A Cross- Sectional Study in Older Adolescents
Bibliographic record
Abstract
Health literacy (HL) is hypothesized to be associated with physical literacy (PL), but studies have rarely examined this association in adolescents. This study aimed to investigate the possible relationships between PL and physical activity levels (PAL), with HL in high-school adolescents. The participants in this cross-sectional study were high school students (n=204; 100 females; 16 to 19 years of age). Variables included evaluation of the HL, PL, and PAL. The Physical Activity Questionnaire for Adolescents was used for analysis of the PAL. PL was assessed by the Canadian Assessment of Physical Literacy, and the Physical Literacy Assessment of Youth (PLAYself). HL was evaluated using the European Health Literacy Survey Questionnaire. Univariate and multivariate correlations were calculated for the total sample and stratified by gender. Boys had greater PAL than girls (t test =6.76, p<0.001), but no significant gender differences were found in PL and HL. The results showed no significant association between PL and HL in boys. PL was significantly associated with HL in girls (17% of the explained variance, p<0.001), with PLAYself being a significant partial regressor (Beta =0.38, p<0.001). Due to the established gender-specific associations between HL and PL, in developing and implementing educational strategies aimed at improving PL and HL in adolescents, a gender-specific approach is warranted.
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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 | 0.002 | 0.005 |
| 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".