Validation of the Italian Translation and Cultural Adaptation of the Canadian Assessment of Physical Literacy-2 (CAPL-2) Questionnaire for Children
Bibliographic record
Abstract
BACKGROUND/OBJECTIVES: Physical literacy is a holistic concept promoting lifelong health by considering an individual's lived experience within their cultural context. This necessitates context-specific conceptualizations and pedagogies, highlighting the need for valid assessment tools for physical and sport educators. The Canadian Assessment of Physical Literacy (CAPL-2) is a well-known validated tool. This study aimed to validate the Italian translation and cultural adaptation of the CAPL-2 questionnaire for children aged 8-12. METHODS: ) completed the adapted CAPL-2 questionnaire twice over 10 days under supervision. The internal consistency of CAPL-2 was assessed with Cronbach's alpha. ROC curve analysis and AUC evaluated the CAPL-2's ability to predict adherence to WHO physical activity guidelines based on self-reported activity. RESULTS: Results showed high internal consistency for the motivation and confidence domain (Cronbach's α: 0.88-0.97) but lower consistency for the knowledge and understanding domain (Cronbach's α: 0.20-0.34). Despite this, the CAPL-2 questionnaire demonstrated high predictive performance in identifying children active for at least 5 days (AUC: 0.95) or 6 days (AUC: 0.89). CONCLUSIONS: The Italian version of CAPL-2 is a reliable tool for assessing physical literacy in Italian children aged 8 to 12, addressing key aspects such as motivation, confidence, physical skills, understanding of physical activity, and daily habits. It offers a valuable and culturally adapted instrument for trainers, teachers and educators in physical activity and sport contexts.
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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 | 0.011 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".