Early detection of autism spectrum condition is crucial for children to maximally benefit from early intervention. The study examined a machine learning model predicting the increased likelihood for autism from wellness records from 0 to 24 months. The study included 591,989 non-autistic and 12,846 autistic children. A gradient boosting model with…

Children with autism spectrum disorder from low-income, minority families or those with limited English proficiency are diagnosed at a later age, or not at all, compared with their more advantaged peers. The Developmental Check-In is a new tool that could potentially be used to screen for autism that uses pictures to illustrate target behaviors.…

This study investigated language profiles in a community-based sample of 104 children aged 1-3 years who had been diagnosed with autism spectrum disorder using "Diagnostic and Statistical Manual of Mental Disorders" (5th ed.) diagnostic criteria. Language was assessed with the Mullen scales, Preschool Language Scale, fifth edition, and…

While various screening instruments for autism spectrum disorders are widely used in diagnostic assessments, their psychometric properties have not been simultaneously evaluated in the outpatient setting where these instruments are used most. In this study, we tested the Ritvo Autism Asperger Diagnostic Scale-Revised and two short versions of the…

The Modified Checklist for Autism in Toddlers (M-CHAT) was used to screen younger (16-23 months) versus older (24-30 months) high- and low-risk toddlers. Refusal rates for follow-up interview showed no group differences, but parents of younger/low-risk children were more likely to refuse evaluation than parents of high-risk children. PPP for an…