Disentangling global and domain‐level adaptive behavior trajectories among children with autism spectrum disorder
Bibliographic record
Abstract
BACKGROUND: Heterogeneity in adaptive behavior abilities among people with autism spectrum disorder (ASD) is expressed not only as uneven levels of impairment across domains, but also in the developmental trajectories of adaptive skills. We studied the question of whether, after accounting for global adaptive behavior development, we find evidence of heterogeneity in the trajectories of specific domains of adaptive behavior. METHODS: A sample of 504 children with ASD was obtained by combining data from two independent natural history studies conducted in North America. We used a factor of curves model to explain growth between 36 and 138 months in Vineland Adaptive Behavior Scales, Second Edition (VABS) age equivalents as a function of domain-specific and global growth processes. RESULTS: The domain-specific trajectories in all three domains (Communication, Daily Living Skills, and Socialization) reflected impairment relative to age expectations as well as slower-than-expected growth with age, and the parameters of these trajectories were moderately-to-strongly correlated across domains. The global adaptive behavior trajectory had an initial (36-41 months of age) developmental level of about 22 age-equivalent months, and eventually slowed after initially increasing by about 6 months each year. The global trajectory accounted for the majority of variance in the domain-level processes; however, additional variance remained (14%-38%) in the domain-level intercepts, slopes, and quadratic processes. CONCLUSIONS: These results extend existing theoretical and empirical support for the hierarchical structure of adaptive behavior to include its development over time in clinical samples of children with ASD. A latent global trajectory may be sufficient to describe the growth of adaptive behavior in children with ASD; however, the remaining domain-specific variability after accounting for global adaptive behavior development allows for the possibility that differential effects of intervention on specific domains may be possible and detectable.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".