Autism Diagnostic Interview-Revised (ADI-R) Algorithms for Toddlers and Young Preschoolers: Application in a Non-US Sample of 1,104 Children
de Bildt, Annelies; Sytema, Sjoerd; Zander, Eric; Bölte, Sven; Sturm, Harald; Yirmiya, Nurit; Yaari, Maya; Charman, Tony; Salomone, Erica; LeCouteur, Ann; Green, Jonathan; Bedia, Ricardo Canal; Primo, Patricia García; van Daalen, Emma; de Jonge, Maretha V.; Guðmundsdóttir, Emilía; Jóhannsdóttir, Sigurrós; Raleva, Marija; Boskovska, Meri; Rogé, Bernadette; Baduel, Sophie; Moilanen, Irma; Yliherva, Anneli; Buitelaar, Jan; Oosterling, Iris J.
(2015) Journal of Autism and Developmental Disorders, volume 45, issue 7, pp. 2076 - 2091
(Article)
Abstract
The current study aimed to investigate the Autism Diagnostic Interview-Revised (ADI-R) algorithms for toddlers and young preschoolers (Kim and Lord, J Autism Dev Disord 42(1):82–93, 2012) in a non-US sample from ten sites in nine countries (n = 1,104). The construct validity indicated a good fit of the algorithms. The diagnostic validity
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was lower, with satisfactorily high specificities but moderate sensitivities. Young children with clinical ASD and lower language ability were largely in the mild-to-moderate or moderate-to-severe concern ranges of the ADI-R, nearly half of the older and phrase speech ASD-group fell into the little-to-no concern range. Although broadly the findings support the toddler algorithms, further work is required to understand why they might have different properties in different samples to further inform research and clinical use.
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Keywords: Assessment, Autism spectrum disorders, Early diagnosis, Developmental and Educational Psychology, Journal Article, Research Support, Non-U.S. Gov't
ISSN: 0162-3257
Publisher: Springer New York
(Peer reviewed)
