Clinical genetic studies confirm the broader autism phenotype (BAP) in some relatives of individuals with autism, but there are few standardized assessment measures. We developed three BAP measures (informant interview, self-report interview, and impression of interviewee observational scale) and describe the development strategy and findings from the interviews. International Molecular Genetic Study of Autism Consortium data were collected from families containing at least two individuals with autism. Comparison of the informant and self-report interviews was restricted to samples in which the interviews were undertaken by different researchers from that site (251 UK informants, 119 from the Netherlands). Researchers produced vignettes that were rated blind by others. Retest reliability was assessed in 45 participants. Agreement between live scoring and vignette ratings was very high. Retest stability for the interviews was high. Factor analysis indicated a first factor comprising social-communication items and rigidity (but not other repetitive domain items), and a second factor comprised mainly of reading and spelling impairments. Whole scale Cronbach's alphas were high for both interviews. The correlation between interviews for factor 1 was moderate (adult items 0.50; childhood items 0.43); Kappa values for between-interview agreement on individual items were mainly low. The correlations between individual items and total score were moderate. The inclusion of several factor 2 items lowered the overall Cronbach's alpha for the total set. Both interview measures showed good reliability and substantial stability over time, but the findings were better for factor 1 than factor 2. We recommend factor 1 scores be used for characterising the BAP.
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http://dx.doi.org/10.1002/aur.1466 | DOI Listing |
Mayo Clin Proc Digit Health
December 2024
Department Radiology, Stanford University, Stanford, CA.
Artificial intelligence (AI) and machine learning (ML) are driving innovation in biosciences and are already affecting key elements of medical scholarship and clinical care. Many schools of medicine are capitalizing on the promise of these new technologies by establishing academic units to catalyze and grow research and innovation in AI/ML. At Stanford University, we have developed a successful model for an AI/ML research center with support from academic leaders, clinical departments, extramural grants, and industry partners.
View Article and Find Full Text PDFPsychiatry Res
January 2025
Key Laboratory of Brain, Cognition and Education Sciences, Ministry of Education, Institute for Brain Research and Rehabilitation, Guangdong Key Laboratory of Mental Health and Cognitive Science, South China Normal University, Guangzhou 510630, China. Electronic address:
Background: Early screening for autism spectrum disorder (ASD) is crucial, yet current assessment tools in Chinese primary child care are limited in efficacy.
Objective: This study aims to employ machine learning algorithms to identify key indicators from the 20-item Modified Checklist for Autism in Toddlers, revised (M-CHAT-R) combining with ASD-related sociodemographic and environmental factors, to distinguish ASD from typically developing children.
Methods: Data from our prior validation study of the Chinese M-CHAT-R (August 2016-March 2017, n = 6,049 toddlers) were reviewed.
Behav Anal Pract
December 2024
Department of Pediatrics, Division of Autism and Related Disabilities, Emory School of Medicine, 1920 Briarcliff Road, Atlanta, GA 30329 USA.
Unlabelled: Naturalistic developmental behavioral intervention (NDBI) supports early social communication skills in young autistic children. Given their emphasis on child-led learning opportunities, NDBI is thought to be a socially valid approach to autism early intervention. Applied behavior analysis (ABA) practices could be an ideal setting to increase access to NDBIs for young autistic children; however, current ABA services continue to rely primarily on structured and adult-led approaches to teaching, including discrete trial training (DTT), which have been criticized for their intensity, limitations in skill generalization, and possible harms.
View Article and Find Full Text PDFSensors (Basel)
December 2024
Graduate Institute of Biomedical Sciences, China Medical University, Taichung 404, Taiwan.
Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by deficits in social interaction and communication. While many studies suggest that individuals with ASD struggle with emotion processing, the association between emotion processing and autistic traits in non-clinical populations is still unclear. We examine whether neurotypical adults' facial emotion recognition and expression imitation are associated with autistic traits.
View Article and Find Full Text PDFBrain Sci
December 2024
Leaps and Bounds Exceptional Services ABA (Applied Behaviour Analysis) Program, Leaps and Bounds Clinic, 13045 Jane Street, King City, ON L7B 1A3, Canada.
Background/objectives: Autism Spectrum Disorder (ASD) are neurodevelopmental disorders marked by challenges in social interaction, communication, and repetitive behaviors. People with ASD may exhibit repetitive behaviors, unique ways of learning, and different ways of interacting with the world. The term "spectrum" reflects the wide variability in how ASD manifests in individuals, including differences in abilities, symptoms, and support needs, and conditions characterized by difficulties in social interactions, communication, restricted interests, and repetitive behaviors.
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