Defining the Optimal Threshold Scores for Adult Autism Subthreshold Spectrum (AdAS Spectrum) in Clinical and General Population.

AdAS Spectrum Autism Spectrum Disorder Autistic traits Diagnostic threshold Psychometric instrument RAADS

Journal

Clinical practice and epidemiology in mental health : CP & EMH
ISSN: 1745-0179
Titre abrégé: Clin Pract Epidemiol Ment Health
Pays: United Arab Emirates
ID NLM: 101245735

Informations de publication

Date de publication:
2020
Historique:
received: 09 07 2020
revised: 27 10 2020
accepted: 23 11 2020
entrez: 15 3 2021
pubmed: 16 3 2021
medline: 16 3 2021
Statut: epublish

Résumé

The Adult Autism Subthreshold Spectrum (AdAS Spectrum) is a recently developed instrument tailored to assess the broad range of full-threshold as well as sub-threshold manifestations related to the autism spectrum. Although it has proved to be a valuable instrument for quantitative assessment of autistic symptoms, the AdAS Spectrum still lacks validated diagnostic thresholds. The aim of this study was to define the best cut-off scores of the AdAS Spectrum for determining the presence of subthreshold autistic traits as well as a clinically significant autism spectrum disorder (ASD). Our sample was composed of 39 patients with full-blown ASD, 73 subjects with autistic traits, and 150 healthy controls. Subjects were evaluated by trained psychiatrists, who performed a clinical diagnosis according to DSM-5 and then assessed with the AdAS Spectrum and the Autism Spectrum Quotient. Our results showed that the most discriminant cut-off scores were 70 for identifying subjects with full-blown ASD, and 43 for determining the presence of significant autistic traits. The threshold values proposed here showed satisfying levels of specificity and sensibility, as well as a good agreement with the diagnosis according to DSM-5 criteria, confirming the validity of the AdAS Spectrum as a psychometric tool for measuring ASD-related conditions in the clinical and general population.

Sections du résumé

BACKGROUND BACKGROUND
The Adult Autism Subthreshold Spectrum (AdAS Spectrum) is a recently developed instrument tailored to assess the broad range of full-threshold as well as sub-threshold manifestations related to the autism spectrum. Although it has proved to be a valuable instrument for quantitative assessment of autistic symptoms, the AdAS Spectrum still lacks validated diagnostic thresholds.
OBJECTIVE OBJECTIVE
The aim of this study was to define the best cut-off scores of the AdAS Spectrum for determining the presence of subthreshold autistic traits as well as a clinically significant autism spectrum disorder (ASD).
METHODS METHODS
Our sample was composed of 39 patients with full-blown ASD, 73 subjects with autistic traits, and 150 healthy controls. Subjects were evaluated by trained psychiatrists, who performed a clinical diagnosis according to DSM-5 and then assessed with the AdAS Spectrum and the Autism Spectrum Quotient.
RESULTS RESULTS
Our results showed that the most discriminant cut-off scores were 70 for identifying subjects with full-blown ASD, and 43 for determining the presence of significant autistic traits.
CONCLUSION CONCLUSIONS
The threshold values proposed here showed satisfying levels of specificity and sensibility, as well as a good agreement with the diagnosis according to DSM-5 criteria, confirming the validity of the AdAS Spectrum as a psychometric tool for measuring ASD-related conditions in the clinical and general population.

Identifiants

pubmed: 33719360
doi: 10.2174/1745017902016010204
pii: CPEMH-16-204
pmc: PMC7931149
doi:

Types de publication

Journal Article

Langues

eng

Pagination

204-211

Informations de copyright

© 2020 Dell'Osso et al.

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Auteurs

Liliana Dell'Osso (L)

Department of Clinical and Experimental Medicine, University of Pisa, Pisa, Italy.

Claudia Carmassi (C)

Department of Clinical and Experimental Medicine, University of Pisa, Pisa, Italy.

Ivan Mirko Cremone (IM)

Department of Clinical and Experimental Medicine, University of Pisa, Pisa, Italy.

Dario Muti (D)

Department of Clinical and Experimental Medicine, University of Pisa, Pisa, Italy.

Antonio Salerni (A)

Department of Clinical and Experimental Medicine, University of Pisa, Pisa, Italy.

Filippo Maria Barberi (FM)

Department of Clinical and Experimental Medicine, University of Pisa, Pisa, Italy.

Enrico Massimetti (E)

Department of Clinical and Experimental Medicine, University of Pisa, Pisa, Italy.

Camilla Gesi (C)

Department of Clinical and Experimental Medicine, University of Pisa, Pisa, Italy.

Pierluigi Politi (P)

Department of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy.

Eugenio Aguglia (E)

Department of Clinical and Experimental Medicine, Psychiatry Unit, University of Catania, Catania, Italy.

Mario Maj (M)

Department of Psychiatry, University of Nalpes SUN, Naples, Italy.

Barbara Carpita (B)

Department of Clinical and Experimental Medicine, University of Pisa, Pisa, Italy.

Classifications MeSH