Comparing Motor Skills in Autism Spectrum Individuals With and Without Speech Delay
Bibliographic record
Abstract
Movement atypicalities in speed, coordination, posture, and gait have been observed across the autism spectrum (AS) and atypicalities in coordination are more commonly observed in AS individuals without delayed speech (DSM-IV Asperger) than in those with atypical or delayed speech onset. However, few studies have provided quantitative data to support these mostly clinical observations. Here, we compared perceptual and motor performance between 30 typically developing and AS individuals (21 with speech delay and 18 without speech delay) to examine the associations between limb movement control and atypical speech development. Groups were matched for age, intelligence, and sex. The experimental design included: an inspection time task, which measures visual processing speed; the Purdue Pegboard, which measures finger dexterity, bimanual performance, and hand-eye coordination; the Annett Peg Moving Task, which measures unimanual goal-directed arm movement; and a simple reaction time task. We used analysis of covariance to investigate group differences in task performance and linear regression models to explore potential associations between intelligence, language skills, simple reaction time, and visually guided movement performance. AS participants without speech delay performed slower than typical participants in the Purdue Pegboard subtests. AS participants without speech delay showed poorer bimanual coordination than those with speech delay. Visual processing speed was slightly faster in both AS groups than in the typical group. Altogether, these results suggest that AS individuals with and without speech delay differ in visually guided and visually triggered behavior and show that early language skills are associated with slower movement in simple and complex motor tasks.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".