Screening for Autism Spectrum Disorders With the Social Communication Questionnaire
Bibliographic record
Abstract
The Social Communication Questionnaire (SCQ) is a parent report screening measure for autism spectrum disorders (ASDs) based on the Autism Diagnostic Interview-Revised (ADI-R). To examine its validity in a young sample, the SCQ was given to parents of 151 children at a mean age of 5 years, before assessment in tertiary autism or preschool clinics. Overall sensitivity was .71, the same for both clinics, but specificity was better for the preschool clinic (.62) than for the autism clinic (.53) reflecting fewer false-positives in the former. The "hit rate" was 65% with 28% of the children with autism missed by the SCQ at a cutoff score of 15 (false-negatives) and 38% of the nonautistic misidentified as having an ASD (false-positives). Item validity analysis, contrary to what was previously published, indicated that only 15 or 46% of the items distinguished between children with and without ASD in this much younger sample. False-negatives were somewhat higher functioning. The SCQ would seem to be a useful tool for identifying young children in need of further assessment and assisting in routing them to the appropriate clinic, especially if used in conjunction with a screening by a community professional. There remain questions about the "best" cutoff score to use and whether a shorter version, based on the items that distinguished autistic from nonautistic, would be more reliable and valid with younger children. Furthermore, it may be that an adjusted score is required when parents omit items or with nonverbal children who cannot be scored on some of the items.
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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 | 0.003 | 0.006 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".