The Canadian Agility and Movement Skill Assessment: A Systematic Review on its Psychometric Properties and Discrimination Power
Bibliographic record
Abstract
PurposeTo systematically review the reliability, validity, and discriminatory capacity of the Canadian Agility and Movement Skill Assessment (CAMSA).MethodA comprehensive search of the MEDLINE/PubMed, SPORTDiscus, and Scopus databases was conducted to identify studies providing data on the reliability, validity, or average and dispersion values of the CAMSA test. The quality of the studies reporting CAMSA reliability and validity was assessed using a checklist based on the sample description, time interval, results, and appropriateness of statistics.ResultsOf the initially forty-two studies located, twenty-two full texts were evaluated, with eight studies ultimately selected. Five investigations provided data on CAMSA reliability, and test-retest reliability was evaluated in three studies. Three studies involving 312 participants were pooled to determine the test-retest reliability of CAMSA-skill and CAMSA-time scores. Results indicated poor reliability for the CAMSA-skill score (ICC: 0.662; 95% CI: 0.29-0.86) and good reliability for the CAMSA-time score (ICC: 0.857; 95% CI: 0.76-0.92). Several studies conducted high-quality reliability analyses. Validity findings from five studies suggested moderate concurrent/convergent associations with other motor competence tests (r = 0.38 to 0.77) and some support for face and structural validity, although the overall quality of these studies was low or very low. The review also highlighted CAMSA's lack of discriminatory power.ConclusionCAMSA shows good reliability for some aspects and moderate concurrent/convergent validity. However, concerns remain about its ability to effectively differentiate between demographic groups like age and sex. Further research is needed to fully establish the psychometric properties, especially its discriminatory power.
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 | 0.018 | 0.090 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.006 |
| Bibliometrics | 0.023 | 0.025 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".