The reach-to-grasp movement in infants later diagnosed with autism spectrum disorder: a high-risk sibling cohort study
Bibliographic record
Abstract
BACKGROUND: Although autism spectrum disorder (ASD) is characterized by impairments in social communication and the presence of repetitive behavior and/or restricted interests, there is evidence that motor impairments may be a contributing factor to the ASD phenotype. The purpose of this study was to examine the motor act of reaching-to-grasp in children at high risk (HR; with an older sibling diagnosed with ASD) and low-risk (LR; no family history of ASD) for ASD. METHODS: Children were compared for differences in reaching-to-grasp based on sibling status and diagnostic outcome. Children were enrolled between 6 and 12 months of age and the reach-to-grasp movement was scored at 6, 9, (where available) 12, 15, 18, 24, and 36 months of age using the qualitative Skilled Reaching Rating Scale to determine the presence of any group-, age-, or sex-related differences in the mechanics of the reach-to-grasp movement using a Mixed Models analysis. At 36 months, all children underwent a gold-standard diagnostic assessment, which resulted in three outcome groups: HR children diagnosed with ASD (HR-ASD; n = 10), HR children not diagnosed with ASD (HR-N; n = 10), and low-risk children not diagnosed with ASD (LR; n = 10). RESULTS: The group of children who were later diagnosed with ASD (HR-ASD group) showed higher (worse) total scores on the reach-to-grasp movement, as well as higher scores on the components of Orient, Lift, and Pronate compared to children in the LR and HR-N groups. CONCLUSIONS: Our results support the growing literature indicating that children who are later diagnosed with ASD show impaired early motor performance. These results highlight the importance of early surveillance of children who are at elevated risk for ASD, and early initiatives should focus on early signs of the phenotype, including both movement and sensory differences (prodromal signs) prior to the emergence of diagnostic characteristics.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".