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MUSAD: validation of the music-based scale for autism diagnosis in adults with intellectual disability

Authors:

Abstract

Background: The MUSAD is a semi-structured approach using a music-based interactional framework to assess a broad variety of diagnostic relevant behaviours associated with autism spectrum disorders (ASD). The diagnostic tool was developed to improve diagnostic possibilities in adults with impaired intellectual and verbal abilities. A preliminary study (N = 80) provided first evidence for good feasibility, objectivity, reliability and construct validity. Objective: The ongoing pilot study (2012-2016) aims to investigate the diagnostic validity of the instrument. Methods: All analysis will be applied to an age-, gender-and IQ-matched clinical sample of more than 100 verbal and non-verbal patients with suspected ASD. A factor analysis will be conducted to confirm the structural model of the MUSAD draft version. Items for an appropriate diagnostic algorithm will be selected based on their clinical utility. A ROC analysis will be applied to assess the ability to discriminate between ASD and non-ASD using the best-clinical estimation as reference. Results: Preliminary results gathered in a sample of n = 88 patients using a diagnostic algorithm based on 14 items showed an appropriate sensitivity/specificity of 82/73 %. Verbal abilities were identified as a predictor of the composite score. Therefore, separate diagnostic algorithms will be developed to improve clinical value. The final results of this evaluation will be presented at the EMTC. Conclusions: The MUSAD is a valid approach to support clinicians identifying ASD in adults with a lower level of functioning.
MUSAD - Validation of the Music-based Scale for Autism Diagnosis in adults with
intellectual disability
Thomas Bergmanna,b, Manuel Heinricha,b, Matthias Zieglerc, Isabel Dziobekd, Albert Diefenbachera, Tanja
Sappoka
aDepartment of Psychiatry, Psychotherapy and Psychosomatics, Evangelisches Krankenhaus Königin Elisabeth
Herzberge, Berlin, Germany; bDepartment of Education and Psychology, Freie Universität Berlin, Germany;
cFaculty of Mathematics and Natural Sciences II/ Institute for Psychology, Humboldt Universität zu Berlin,
Germany; dBerlin School of Mind and Brain, Humboldt Universität zu Berlin, Germany
Background: The MUSAD is a semi-structured approach using a music-based interactional framework to assess
a broad variety of diagnostic relevant behaviours associated with autism spectrum disorders (ASD). The
diagnostic tool was developed to improve diagnostic possibilities in adults with impaired intellectual and verbal
abilities. A preliminary study (N = 80) provided first evidence for good feasibility, objectivity, reliability and
construct validity.
Objective: The ongoing pilot study (2012-2016) aims to investigate the diagnostic validity of the instrument.
Methods: All analysis will be applied to an age-, gender- and IQ-matched clinical sample of more than 100
verbal and non-verbal patients with suspected ASD. A factor analysis will be conducted to confirm the structural
model of the MUSAD draft version. Items for an appropriate diagnostic algorithm will be selected based on their
clinical utility. A ROC analysis will be applied to assess the ability to discriminate between ASD and non-ASD
using the best-clinical estimation as reference.
Results: Preliminary results gathered in a sample of n = 88 patients using a diagnostic algorithm based on 14
items showed an appropriate sensitivity/specificity of 82/73 %. Verbal abilities were identified as a predictor of
the composite score. Therefore, separate diagnostic algorithms will be developed to improve clinical value. The
final results of this evaluation will be presented at the EMTC.
Conclusions: The MUSAD is a valid approach to support clinicians identifying ASD in adults with a lower level
of functioning.
Keywords: Autism spectrum disorder, diagnostics, music, adults, intellectual disability.
Funding: This work was supported by the Stiftung Irene gemeinnützige Stiftung zum Wohle autistischer
Menschen, Hamburg, Germany.
*Corresponding author. Email: bergmann.t@t-online.de
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