Early Motor Function of Children With Autism Spectrum Disorder: A Systematic Review
Bibliographic record
Abstract
CONTEXT: Early motor impairments have been reported in children with neurodevelopmental disorders (NDD), but it is not clear if early detection of motor impairments can identify children at risk for NDD or how early such impairments might be detected. OBJECTIVE: To characterize early motor function in children later diagnosed with NDD relative to typically developing children or normative data. DATA SOURCES: The Cumulative Index to Nursing and Allied Health Literature, Embase, Medline, PsycINFO, and Scopus electronic databases were searched. STUDY SELECTION: Eligible studies were required to include an examination of motor function in children (0-24 months) with later diagnosis of NDD by using standardized assessment tools. DATA EXTRACTION: Data were extracted by 4 independent researchers. The quality of the studies was assessed by using the Standard Quality Assessment Criteria for Evaluating Primary Research Papers from a Variety of Fields checklist. RESULTS: Twenty-five studies were included in this review; in most of the studies, the authors examined children with later autism spectrum disorder (ASD). Early motor impairments were detected in children later diagnosed with ASD. The meta-analysis results indicated that differences in fine, gross, and generalized motor functions between the later ASD and typically developing groups increased with age. Motor function across different NDD groups was found to be mixed. LIMITATIONS: Results may not be applicable to children with different types of NDD not reported in this review. CONCLUSIONS: Early motor impairments are evident in children later diagnosed with ASD. More research is needed to ascertain the clinical utility of motor impairment detection as an early transdiagnostic marker of NDD risk.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".