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Parents of 1,150 primary school aged children were sent the CAST questionnaire, with 199 responders and 174 taking part in the full data analysis. The results suggested that, compared to other screening tools currently available, the CAST may be useful for identifying children at risk for autism spectrum disorders, in a mainstream non-clinical sample.
Research-determined cut-offs identify the potential diagnosis of autism spectrum disorder, allowing a standardized assessment of autistic symptoms. The Autism Diagnostic Interview-Revised (ADI-R), a companion instrument, is a structured interview conducted with the parents of the referred individual to cover the subject's full developmental ...
The first stage stratifies children into 3 group- low risk, medium risk, and high risk. Children who are medium risk go to the second stage for further clarification. A child whose score was greater than 3 at the first screening and greater than 2 on the second screening had a 47.5% risk of being diagnosed with autism spectrum disorder. [6]
The WebABLLS is an electronic version of the assessment. It allows parents, teachers, speech pathologists, behavior analysts, and others who design, coordinate, or supervise language or skill-acquisition programs to expedite the development of IEPs, progress reports, and to easily share information about a child.
The Checklist for Autism in Toddlers (CHAT) is a psychological questionnaire designed to evaluate risk for autism spectrum disorder in children ages 18–24 months. The 14-question test is filled out by the parent and a pediatrician or physician and takes approximately 5 minutes to complete. [ 1 ]
The Autism Treatment Evaluation Scale (ATEC) is a 77-item diagnostic assessment tool that was developed by Bernard Rimland and Stephen Edelson at the Autism Research Institute. The ATEC was originally designed to evaluate the effectiveness of autism treatments, but it may also be beneficial as a screening tool for children.
The Ritvo Autism & Asperger Diagnostic Scale (RAADS) is a psychological self-rating scale developed by Riva Ariella Ritvo (NPI UCLA and CSC Yale). An abridged and translated 14 question version was then developed at the Department of Clinical Neuroscience at the Karolinska Institute, to aid in the identification of patients who may have undiagnosed ASD.
Research comparing ADI-R results of autistic children and children with other developmental disorders suggested that individual questions on the interview were slightly more valid when discriminating autism from intellectual disability than the algorithm as a whole. However, further research has led to overall acceptance of the ADI-R algorithm. [3]