Risk assessment for parents who suspect their child has autism spectrum disorder: Machine learning approach

Ayelet Ben-Sasson, Diana L. Robins, Elad Yom-Tov

Research output: Contribution to journalArticlepeer-review

Abstract

Background: Parents are likely to seek Web-based communities to verify their suspicions of autism spectrum disorder markers in their child. Automated tools support human decisions in many domains and could therefore potentially support concerned parents. Objective: The objective of this study was to test the feasibility of assessing autism spectrum disorder risk in parental concerns from Web-based sources, using automated text analysis tools and minimal standard questioning. Methods: Participants were 115 parents with concerns regarding their child's social-communication development. Children were 16- to 30-months old, and 57.4% (66/115) had a family history of autism spectrum disorder. Parents reported their concerns online, and completed an autism spectrum disorder-specific screener, the Modified Checklist for Autism in Toddlers-Revised, with Follow-up (M-CHAT-R/F), and a broad developmental screener, the Ages and Stages Questionnaire (ASQ). An algorithm predicted autism spectrum disorder risk using a combination of the parent's text and a single screening question, selected by the algorithm to enhance prediction accuracy. Results: Screening measures identified 58% (67/115) to 88% (101/115) of children at risk for autism spectrum disorder. Children with a family history of autism spectrum disorder were 3 times more likely to show autism spectrum disorder risk on screening measures. The prediction of a child's risk on the ASQ or M-CHAT-R was significantly more accurate when predicted from text combined with an M-CHAT-R question selected (automatically) than from the text alone. The frequently automatically selected M-CHAT-R questions that predicted risk were: following a point, make-believe play, and concern about deafness. Conclusions: The internet can be harnessed to prescreen for autism spectrum disorder using parental concerns by administering a few standardized screening questions to augment this process.

Original languageEnglish
Article numbere134
JournalJournal of Medical Internet Research
Volume20
Issue number4
DOIs
StatePublished - Apr 2018

Bibliographical note

Funding Information:
The authors received financial support for the research of this paper from the Caesarea Rothschild Institute.

Publisher Copyright:
© Ayelet Ben-Sasson, Diana L Robins, Elad Yom-Tov.

Keywords

  • Autistic disorder
  • Child
  • Early diagnosis
  • Expression of concern
  • Machine learning
  • Parents
  • Screening
  • Technology

ASJC Scopus subject areas

  • Health Informatics

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