The Interrelationship Between Motor Coordination and Adaptive Behavior in Children With Autism Spectrum Disorder
Bibliographic record
Abstract
Objective Children with autism spectrum disorder (ASD) experience significant challenges with their motor coordination. It is not, however, well understood how motor coordination may impact the behavioral functioning of children with ASD. Therefore the purpose of this study was to explore the relationships between motor coordination and adaptive behavior in 7-12 year old children with ASD. Methods Motor coordination was assessed using the Movement Assessment Battery for Children, 2nd Edition (MABC-2) and adaptive behavior was assessed by parental report using the Vineland Adaptive Behavior Scales, 2nd Edition (VABS-2) as part of a larger cross-sectional study. Descriptive characteristics were calculated for MABC-2 and VABS-2 scores and Spearman’s rank order correlation analyses were used to examine the relationship between motor coordination and adaptive behavior. Results On average, the participants (n=26) exhibited significant challenges in regard to their motor coordination with all but two participants classified as having significant motor impairments by scoring at or below the 16th percentile on the MABC-2. Results from the correlation analyses indicated that manual dexterity was positively related to daily living skills (ρ=.58, p<.003), and overall motor coordination was positively related to daily living skills (ρ=.60, p<.003) and overall adaptive behavior (ρ=.57, p<.003). In all instances, better motor coordination was related to more adaptive behaviors. Conclusion These results highlight the profound motor coordination challenges that children with ASD experience and also suggest that these challenges, particularly with manual dexterity, are related to the daily behavior of children with ASD. The interrelatedness of motor and adaptive behavior suggests the need to further explore the impact of motor-based interventions for this population, as well as conduct longitudinal studies to disentangle these relationships.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".