ArticleAutism research : official journal of the International Society for Autism Research2023
Relationship between quantitative digital behavioral features and clinical profiles in young autistic children.
Article in Autism research : official journal of the International Society for Autism Research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
4 citing papers in PubMed.
- Media Equation of the Interaction of Children with Autism Spectrum Disorder: A Proof-of-Concept Approach Using an Equivalence Test in a Within-Subject Design.Journal of autism and developmental disorders · 2025Article
- Autism Digital Phenotyping in Preschool- and School-Age Children.Autism research : official journal of the International Society for Autism Research · 2025Article
- Article
- Early detection of autism using digital behavioral phenotyping.Nature medicine · 2023Article
Corrections and comments
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Authors and funding
14 authors.
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Abstract
Early behavioral markers for autism include differences in social attention and orienting in response to one's name when called, and differences in body movements and motor abilities. More efficient, scalable, objective, and reliable measures of these behaviors could improve early screening for autism. This study evaluated whether objective and quantitative measures of autism-related behaviors elicited from an app (SenseToKnow) administered on a smartphone or tablet and measured via computer vision analysis (CVA) are correlated with standardized caregiver-report and clinician administered measures of autism-related behaviors and cognitive, language, and motor abilities. This is an essential step in establishing the concurrent validity of a digital phenotyping approach. In a sample of 485 toddlers, 43 of whom were diagnosed with autism, we found that CVA-based gaze variables related to social attention were associated with the level of autism-related behaviors. Two language-related behaviors measured via the app, attention to people during a conversation and responding to one's name being called, were associated with children's language skills. Finally, performance during a bubble popping game was associated with fine motor skills. These findings provide initial support for the concurrent validity of the SenseToKnow app and its potential utility in identifying clinical profiles associated with autism. Future research is needed to determine whether the app can be used as an autism screening tool, can reliably stratify autism-related behaviors, and measure changes in autism-related behaviors over time.
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Registered trials
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