Relationship between quantitative digital behavioral features and clinical profiles in young autistic children

Marika Coffman, J. Matias Di Martino, Rachel Aiello, Kimberly L.H. Carpenter, Zhuoqing Chang, Scott Compton, Brian Eichner, Steve Espinosa, Jacqueline Flowers, Lauren Franz, Sam Perochon, Pradeep Raj Krishnappa Babu, Guillermo Sapiro, Geraldine Dawson

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

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.

Original languageEnglish
Pages (from-to)1360-1374
Number of pages15
JournalAutism Research
Volume16
Issue number7
DOIs
StatePublished - Jul 2023
Externally publishedYes

Keywords

  • autism
  • computer vision
  • digital phenotyping
  • screening

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