ERIC Number: EJ1223558
Record Type: Journal
Publication Date: 2019-Sep
Pages: 21
Abstractor: As Provided
ISBN: N/A
ISSN: ISSN-0162-3257
EISSN: N/A
Developing a Diagnostic Algorithm for the Music-Based Scale for Autism Diagnostics (MUSAD) Assessing Adults with Intellectual Disability
Bergmann, Thomas; Heinrich, Manuel; Ziegler, Matthias; Dziobek, Isabel; Diefenbacher, Albert; Sappok, Tanja
Journal of Autism and Developmental Disorders, v49 n9 p3732-3752 Sep 2019
Initial studies have presented the "Music-based Scale for Autism Diagnostics" (MUSAD) as a promising DSM-5-based observational tool to identify autism spectrum disorder (ASD) in adults with intellectual disability (ID). The current study is the first to address its clinical utility in a new sample of 124 adults with ID (60.5% diagnosed with ASD). The derived diagnostic algorithm differentiated well between individuals with and without ASD (sensitivity 79%, specificity 74%, area under the curve = 0.81). Inter-rater reliability, assessed by the scorings of four independent experts in 22 consensus cases, was excellent (ICC = 0.92). Substantial correlations with scores from other ASD-specific measures indicated convergent validity. The MUSAD yields accurate and reliable scores, supporting comprehensive ASD diagnostics in adults with ID.
Descriptors: Autism, Pervasive Developmental Disorders, Adults, Intellectual Disability, Diagnostic Tests, Music, Mathematics, Interrater Reliability, Test Validity
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Publication Type: Journal Articles; Reports - Research
Education Level: N/A
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A
Grant or Contract Numbers: N/A