Structural content and psychometric properties of fundamental movement skills assessment scales for school-age children based on ICF-CY: a systematic review
Bibliographic record
Abstract
Objective To rexplore the content structure characteristics and psychometric properties of assessment scales for fundamental movement skills (FMS) in school-aged children, based on International Classification of Functioning, Disability and Health-Children and Youth Version (ICF-CY) framework. Methods Literatures on assessment scales for FMS in school-aged children were retrieved from PubMed, Science Direct, Web of Science, EMBase, PsycINFO, CNKI and Wanfang data from inception to July, 2025. The contents of the included scales were analyzed using the ICF-CY linking rule. The COSMIN RoB tool was used to assess the psychometric properties of the scales, and the GRADE system was applied to evaluate the overall quality of evidence. Results A total of 29 studies were included, involving six assessment scales: Bruininks-Oseretsky Test of Motor Proficiency-2 (BOT-2), Canadian Assessment of Movement Skill and Agility (CAMSA), Körperkoordinationstest für Kinder (KTK), Movement Assessment Battery for Children-2 (MABC-2), Motorische Basiskompetenzen test Battery (MOBAK), and Test of Gross Motor Development-3 (TGMD-3). In the ICF-CY linking analysis, all six tools addressed joint mobility functions (b710) and joint stability functions (b715), while five of them also involved hand and arm use (d445). The number of linked items ranged from 5 to 11. BOT-2 and TGMD-3 linked to 11 items, showing broad coverage; BOT-2 focused more on the body function dimension, whereas TGMD-3 emphasized activity and participation dimensions, especially the performance of hand function in daily activities. In bias risk assessment, TGMD-3 showed the lowest risk (50% rated A and 50% rated B), while MABC-2 had the highest proportion of C ratings (55.6%), followed by BOT-2 (33.3%). In evidence grading, TGMD-3 was rated high quality, KTK moderate, BOT-2 and CAMSA low, and MABC-2 and MOBAK very low. Conclusion TGMD-3 is recommended as the primary tool for assessing FMS in school-aged children for broad coverage of ICF-CY items, strong psychometric properties and high evidence quality. KTK, with moderate evidence quality, may serve as a secondary option, but should be used cautiously in China. Although CAMSA is easy to administer, its validity and reliability are low, so it is only suitable for rapid classroom screening. BOT-2, despite covering more ICF-CY items, has a higher bias risk and low evidence quality. MOBAK and MABC-2 have very low evidence quality and are not recommended for current use.
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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 | 0.017 | 0.076 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.009 |
| Bibliometrics | 0.021 | 0.018 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 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".