Lagging skills contribute to challenging behaviors in children with autism spectrum disorder without intellectual disability
Bibliographic record
Abstract
Many children with autism spectrum disorder display challenging behaviors. These behaviors are not limited to those with cognitive and/or language impairments. The Collaborative and Proactive Solutions framework proposes that challenging behaviors result from an incompatibility between environmental demands and a child's "lagging skills." The primary Collaborative and Proactive Solutions lagging skills-executive function, emotion regulation, language, and social skills-are often areas of weakness for individuals with autism spectrum disorder. The purpose of this study was to evaluate whether these lagging skills are associated with challenging behaviors in youth with autism spectrum disorder without intellectual disability. Parents of 182 youth with autism spectrum disorder (6-15 years) completed measures of their children's challenging behaviors, executive function, language, emotion regulation, and social skills. We tested whether the Collaborative and Proactive Solutions lagging skills predicted challenging behaviors using multiple linear regression. The Collaborative and Proactive Solutions lagging skills explained significant variance in participants' challenging behaviors. The Depression (emotion regulation), Inhibit (executive function), and Sameness (executive function) scales emerged as significant predictors. Impairments in emotion regulation and executive function may contribute substantially to aggressive and oppositional behaviors in school-age youth with autism spectrum disorder without intellectual disability. Treatment for challenging behaviors in this group may consider targeting the incompatibility between environmental demands and a child's lagging skills.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".