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The Childhood Autism Rating Scale (CARS) is a behavior rating scale intended to help diagnose autism. CARS was developed by Eric Schopler , Robert J. Reichler , and Barbara Rochen Renner . The scale was designed to help differentiate children with autism from those with other developmental delays, such as intellectual disability .
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.
Among these measurements, the Autism Diagnostic Interview-Revised (ADI-R) and the Autism Diagnostic Observation Schedule (ADOS) are considered the "gold standards" for assessing autistic children. [ 24 ] [ 25 ] The ADI-R is a semi-structured parent interview that probes for symptoms of autism by evaluating a child's current behavior and ...
The Child and Adolescent Symptom Inventory (CASI) is a behavioral rating checklist created by Kenneth Gadow and Joyce Sprafkin that evaluates a range of behaviors related to common emotional and behavioral disorders identified in the Diagnostic and Statistical Manual of Mental Disorders (DSM), including attention deficit hyperactivity disorder, oppositional defiant disorder, conduct disorder ...
assess autism in children, adolescents, and adults The Autism Diagnostic Observation Schedule ( ADOS ) is a standardized diagnostic test for assessing autism spectrum disorder . The protocol consists of a series of structured and semi-structured tasks that involve social interaction between the examiner and the person under assessment.
The scale is available in forms for teachers as well as parents, and like the Gilliam Autism Rating Scale it is comparatively less complicated to administer and score than other tests such as the Autism Diagnostic Observation Schedule or the Autism Diagnostic Interview — Revised (although both of these more complex tests are increasingly used ...
Achenbach used machine learning and principal component analysis when developing the ASEBA in order to cluster symptoms together when forming the assessment's eight categories. This approach ignored the syndrome clusters found in the DSM-I, instead relying on patterns found in case records of children with identified psychopathologies.
Children will transition between different environments many times as they grow. For example, a child will transition into elementary or high school or from one service setting or agency to another. Attention to these transitions of children with disabilities has been identified as an important role for health care providers. [16]