Motor skills of toddlers with autism spectrum disorders
Bibliographic record
Abstract
With increased interest in the early diagnosis and treatment of children with autism spectrum disorders (ASD), more attention has been called to the motor skills of very young children with ASD. This study describes the gross and fine motor skills of a cross-sectional group of 162 children with ASD between the ages of 12 and 36 months, as well as a subset of 58 children followed longitudinally. Gross motor and fine motor age equivalent scores were obtained for all children. A 'motor difference' variable was calculated for each child's gross and fine motor skills by taking the absolute difference of the children's age equivalent motor score and their respective chronological age. In Study 1 (the cross-sectional analysis), ANCOVA (co-varied for nonverbal problem solving) revealed significant group differences in the gross motor and fine motor age difference variables. Post-hoc analysis revealed that gross motor and fine motor differences became significantly greater with each 6-month period of chronological age. In Study 2, 58 children were measured twice, an average of 12 months apart. Results indicate that the gross motor and fine motor difference scores significantly increased between the first and second measurements. The importance of addressing motor development in early intervention treatments is discussed.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".