Utility of the Autism Diagnostic Observation Schedule and the Brief Observation of Social and Communication Change for Measuring Outcomes for a <scp>Parent‐Mediated</scp> Early Autism Intervention
Bibliographic record
Abstract
Measuring outcomes for autistic children following social communication interventions is an ongoing challenge given the heterogeneous changes, which can be subtle. We tested and compared the overall and item-level intervention effects of the Brief Observation of Social Communication Change (BOSCC), Autism Diagnostic Observation Schedule (ADOS-2) algorithm, and ADOS-2 Calibrated Severity Scores (CSS) with autistic children aged 2-5 years from the Preschool Autism Communication Trial (PACT). The BOSCC was applied to Module 1 ADOS assessments (ADOS-BOSCC). Among the 117 children using single or no words (Module 1), the ADOS-BOSCC, ADOS algorithm, and ADOS CSS each detected small non-significant intervention effects. However, on the ADOS algorithm, there was a medium significant intervention effect for children with "few to no words" at baseline, while children with "some words" showed little intervention effect. For the full PACT sample (including ADOS Module 2, total n=152), ADOS metrics evidenced significant small (CSS) and medium (algorithm) overall intervention effects. None of the Module 1 item-level intervention effects reached significance, with largest changes observed for Gesture (ADOS-BOSCC and ADOS), Facial Expressions (ADOS), and Intonation (ADOS). Significant ADOS Module 2 item-level effects were observed for Mannerisms and Repetitive Interests and Stereotyped Behaviors. Despite strong psychometric properties, the ADOS-BOSCC was not more sensitive to behavioral changes than the ADOS among Module 1 children. Our results suggest the ADOS can be a sensitive outcome measure. Item-level intervention effect plots have the potential to indicate intervention "signatures of change," a concept that may be useful in future trials and systematic reviews. LAY SUMMARY: This study compares two outcome measures in a parent-mediated therapy. Neither was clearly better or worse than the other; however, the Autism Diagnostic Observation Schedule produced somewhat clearer evidence than the Brief Observation of Social Communication Change of improvement among children who had use of "few to no" words at the start. We explore which particular behaviors are associated with greater improvement. These findings can inform researchers when they consider how best to explore the impact of their intervention.
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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 | 0.020 | 0.033 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| 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".