Screening Options in Autism Telediagnosis: Examination of TAP, M-CHAT-R, and DCI Concordance and Predictive Value in a Telediagnostic Model.
Amy S Weitlauf, Tori Foster, James C Slaughter and 7 others
PMID 38833028WHAT IT FOUND
The Developmental Check-In predicted autism diagnosis better than the M-CHAT-R in a telediagnostic model.
Its Talk and Social subdomains were the strongest predictors, raising the probability of identifying autism from .50 to .76 compared to .66 for the M-CHAT-R.
Key findings
01The DCI subdomains model predicted autism diagnosis with a C-index of .76, outperforming the M-CHAT-R model which had a C-index of .66.
02Within the DCI, the Social and Talk subdomains were the best predictors of diagnostic status, while Play and Behavior subdomains did not predict strongly.
03DCI Behavior scores were elevated across both children with and without autism, suggesting this subdomain may reflect general behavioral concerns or caregiver distress rather than autism-specific traits.
STILL TO COME
How it was doneWhat they foundWhat it means for SLPs
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What it does not show
The sample had an extremely high rate of autism diagnosis (88.9%), which limits the ability to assess the true specificity of the tools in a general population. The study population was approximately 80% White and 90% Non-Hispanic, limiting generalizability to more diverse communities. The DCI was optional, meaning data was missing for 77 of the 361 children who completed the TAP. The TAP validation was ongoing at the time of the study, and the diagnostic decision was based on a comprehensive clinical evaluation, not solely on the TAP score.
Declared interests
The authors have no financial relationships or conflicts of interest relevant to this article to disclose.
The easy way to misread this
Do not use the DCI Behavior subdomain as a specific indicator for autism in your clinical decision-making. Scores were elevated in both children with and without autism, suggesting it captures general behavioral concerns or caregiver stress rather than autism-specific traits.
Summarised by AI from the full paper, without a clinician reviewing it. Check it against the source before it changes what you do. Read it on PubMed →