Children with autism exhibit similar longitudinal changes in core symptoms when placed in special or mainstream education settings
Bibliographic record
Abstract
Children with autism spectrum disorder (ASD) are often placed in inclusive mainstream education (ME) or exclusive special education (SE) settings. While ME settings usually offer less-intensive and structured intervention programs than SE settings, they offer more exposure to typically developing peers. A total of 121 children (2–5 years old) with ASD, 85 in SE and 36 in ME, completed two Autism Diagnostic Observation Schedule, 2nd edition (ADOS-2) assessments. Repeated-measures analysis of covariance (ANCOVA) analyses were used to assess longitudinal changes in ADOS-2 calibrated severity scores (CSS) and language production (estimated from the ADOS-2), while accounting for baseline cognitive scores, age of diagnosis, and parent-reported intensity of intervention. Longitudinal changes in ADOS CSS did not differ significantly across educational settings but were strongly associated with the age of diagnosis, demonstrating that children diagnosed earlier improved more regardless of educational settings. These findings suggest that children with ASD placed in SE and ME exhibit similar longitudinal changes in core ASD symptoms. Further studies comparing additional outcome measures such as cognitive abilities and adaptive behaviors are highly warranted for establishing placement recommendations and public health policies. Lay abstract Today, children with autism spectrum disorder (ASD) are placed in mainstream or special education settings somewhat arbitrarily with no clear clinical recommendations. Here, we compared changes in core ASD symptoms, as measured by the Autism Diagnostic Observation Schedule, 2nd edition (ADOS-2) clinical assessment, across ASD preschool children placed in special or mainstream education. Longitudinal changes in ADOS-2 scores did not differ significantly across settings over a 1- to 2-year period. While some children improved in core ASD symptoms, others deteriorated in both settings. This highlights the need to identify specific criteria for establishing meaningful placement recommendations.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 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".