EXAMINING THE VALIDITY OF NOVEL DIGITAL APPROACHES TO THE EARLY IDENTIFICATION OF AUTISM SPECTRUM DISORDER

EXAMINING THE VALIDITY OF NOVEL DIGITAL APPROACHES TO THE EARLY IDENTIFICATION OF AUTISM SPECTRUM DISORDER

Early identification and treatment of young children with ASD represents a significant public health and clinical care challenge. There is strong evidence that young children with ASD receiving early behavioral intervention services demonstrate substantial gains in functioning. However, current assessment methods provide information that is difficult to interpret and yield a large number of false positives. The Digital version of the Modified Checklist for Autism in Toddlers (DM-CHAT) and Digital ASD Risk Assessment (DARA) are being developed through this project to allow pediatricians and pediatric nursing staff to more quickly and accurately screen for ASD, thus making referrals for comprehensive autism evaluation only when necessary. By reducing the number of false positives and unnecessary referrals to ASD experts for comprehensive evaluation, the technology enables a more efficient use of limited resources, particularly in underserved or rural areas where access to ASD experts is often in short supply.

Geraldine Dawson, Dept. of Psychiatry and Behavioral Sciences, Psychology and Neuroscience (Principal Investigator)

Helen Egger, Dept. of Psychiatry and Behavioral Sciences

Guillermo Sapiro, Pratt School of Engineering and Computer Sciences

Jeffrey Baker, Dept. of Pediatrics

Robert Calderbank, Dept. of Computer Science; Information Initiative at Duke

Kathleen Campbell, Dept. of Pediatrics

Kimberly Carpenter, Dept. of Psychiatry and Behavioral Sciences

Saritha Vermeer, Dept. of Psychiatry and Behavioral Sciences

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