Psychometric properties of the knowledge and understanding questionnaire of the canadian assessment of physical literacy-2 in low-income brazilian children
Bibliographic record
Abstract
This study aimed to translate and cross-culturally adapt the Physical Literacy Knowledge (PLK) questionnaire from Canadian Assessment of Physical Literacy-2 for Portuguese version, and to evaluate its psychometric properties (construct validation, content, composite reliability, measurement invariance) in low-income Brazilian children. The sample comprised of 562 children (247 girls), aged between 8.00 and 12.99 years-old (10.20±1.20 years), enrolled in the 12 public-school in Lagoa do Carro city, Pernambuco, Brazil. A translation and cross-cultural adaptation of the PLK questionnaire was carried out. Content validity was determined by calculating the content validity coefficient, which assesses the relevance, clarity and pertinence of total (CVCt) and each question individually (CVCi). The dimensional structure of the PLK and alternative models were considered with first and second order models. Internal consistency was assessed using composite reliability. Structural invariance (configural, metric, scalar and strict) between sexes was also assessed using a multigroup factor analysis. Content validity was considered acceptable, varying between 0.88 and 1.00 for CVCi, and 0.91, 0.94 and 0.99 for clarity, pertinence and relevance in the CVCt, respectively. Construct validity was considered adequate, with 3 dimensions and 9 items model being the most appropriate [χ²(df)=34.01(24); CFI=0.92; TLI=0.87; RMSEA=0.03; SRMR=0.04; 90%CIRMSEA=0.00-0.05]. The questionnaire was structurally invariant (all ΔCFI<0.05). Based on the findings, the PLK questionnaire has adequate psychometric properties to assess the cognitive domain of Physical Literacy in low-income Brazilian children. Key-words: Physical Literacy; Cognition; Children; Psychometry; Child Development.
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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 | 0.006 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".