Motor function tests for 0-2-year-old children - a systematic review.
Bibliographic record
Abstract
INTRODUCTION: There is no evidence on how motor function is best evaluated in children in a low-risk setting. The method used in the Danish Preventive Child Health Examination Programme (DPCHEP) in general practise has not been validated. The objective of this review was to identify existing motor function tests for 0-2-year-old children that were validated for use in the background population and which are suitable for use in the DPCHEP. METHODS: This systematic review was conducted in accordance with the PRISMA guidelines. A systematic literature search was performed in PubMed, Embase, SwedMed, PsycInfo and CINAHL in accordance with the inclusion and exclusion criteria. RESULTS: Five motor function tests were identified. The Alberta Infant Motor Scale (AIMS) exclusively assesses motor function, the Harris Infant Neuromotor Assessment also assesses cognition and the Early Motor Questionnaire (EMQ) additionally assesses perception-action integration skills. The Ages and Stages Questionnaire (ASQ) and The Brigance Infant and Toddler Screen include further aspects of development. All test methods, except for the AIMS, are based on parent involvement. CONCLUSIONS: For implementation in the DPCHEP, five motor function tests were potentially adequate. However, the time consumption and extensive use of tools render three of the five tests unsuitable for implementation in the existing programme. The two remaining tests, the ASQ and the EMQ, are parent questionnaires. We suggest that these should be pilot tested with a view to their subsequent implementation in the DPCHEP. It may be considered to present the test elements in a more manageable and systematic way, possibly with illustrations.
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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 | 0.039 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.006 |
| Bibliometrics | 0.007 | 0.006 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".