Translation and validation of the Canadian assessment of physical literacy-2 in a Danish sample
Bibliographic record
Abstract
BACKGROUND: The aim of this study was to translate the Canadian Assessment of Physical Literacy, second edition (CAPL-2) into Danish language, adapt it to Danish context and to test the measurement properties on a sample of Danish school children. METHODS: The CAPL-2 measurement tool was translated into Danish language and adapted for the Danish context. This Danish version of the CAPL-2 was then tested on 891 Danish school children from 50 classes in 12 different schools. RESULTS: Confirmatory factor analysis using the four-factor model, as suggested by the CAPL-2 original developers, showed an acceptable model fit for the Danish version (CFI = .973; TLI = .957; RMSEA = 0.040 (90% CI 0.033-0.054); SRMR = 0.040). Positive significant correlations between the domains were found. The domains as well as the total CAPL-2 score were found to be positively associated with physical education teachers' assessment of their pupil's in four central aspects of PL (i.e. enjoyment, confidence, motor skills, and diversity) indicating predictive validity. High internal consistency of the instrument used to measure motivation and confidence domain were found. CONCLUSION: The translated and context-adapted Danish version of CAPL-2 is a valid and reliable measurement tool ready to use in Danish research studies.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.009 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".