Spanish Translation and Cultural Adaptation of the Canadian Assessment of Physical Literacy-2 (CAPL-2) Questionnaires
Bibliographic record
Abstract
Background: This study aimed to translate and culturally adapt the questionnaires belonging to the Canadian Assessment of Physical Literacy-2 (CAPL-2) into Spanish and to explore the reliability for its use in children and adolescents aged from 8 to 12 years. Methods: The CAPL-2 questionnaires were translated using the translation–back-translation methodology into Spanish and adapted to the Spanish context. The test–retest reliability and internal consistency of the CAPL-2 questionnaires of this Spanish version were analysed in 57 schoolchildren from a school in the region of Extremadura (Spain). Results: High internal consistency (α = 0.730 to 0.970) and test–retest reliabilities ranging from moderate to almost perfect in the knowledge and understanding domain (ICC = 0.486 to 0.888); from substantial to almost perfect in the motivation and confidence domain (ICC = 0.720 to 0.981); and almost perfect in the daily activity domain (ICC = 0.975) were found. The test–retest correlation was significantly weak to strong (r = 0.266 to 0.815) in both the motivation and confidence and knowledge and understanding domains, except for the third predilection item and the muscular endurance question. Significant test–retest differences were observed in the first intrinsic motivation item (p = 0.027) and the knowledge and understanding domain total score (p = 0.014). Conclusion: The Spanish version of the CAPL-2 questionnaires, translated and adapted to the context, are reliable measurement tools, serving to complete the full adaptation of the CAPL-2 test battery for use in children aged 8 to 12 years.
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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 | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".