A digital health approach to early identification and outcome monitoring in autism

NIH RePORTER · NIH · P50 · $43,378 · view on reporter.nih.gov ↗

Abstract

ABSTRACT – Project 1 The overall goal of the Duke Autism Center of Excellence is to use a translational digital health and computational approach to address the critical need for more effective autism screening tools, objective outcome measures, and brain-based biomarkers that can be used in clinical trials with young autistic children. The goal of Project 1 is to evaluate novel digital behavioral assessment tools based on computer vision analysis and machine learning that can be implemented in real-world settings to improve the accuracy of autism screening and enable scalable, objective longitudinal monitoring of children’s behavior and development. Project 1 will recruit a large population of 16- to 30-month-old toddlers through primary care clinics to evaluate the accuracy of a remotely administered novel digital phenotyping application (app) for detecting early signs of autism. The app automatically quantifies direct observations of children’s behavior using computer vision analysis and is deployed on a smartphone or tablet. We will assess the sensitivity, specificity, negative/positive predictive values, and test-retest reliability of the digital phenotyping app for autism detection when delivered by parents at home. We will also assess the app’s usability for longitudinal outcome monitoring of autistic children at 16-30, 36, and 48 months of age by examining its convergent validity compared to standardized clinical measures. With a goal of expanding the types of behavioral measures that could be used for autism screening and outcome monitoring, we will explore the feasibility of using computer vision analysis to measure parent-child interaction from videos recorded at home. Finally, in collaboration with Project 2, we will design an automated clinical decision support for primary care providers that integrates autism screening information with actionable guidance regarding referrals for diagnosis and services and assess its perceived usability. Our long-term vision is to transform how clinical care is delivered by providing innovative solutions that address long-standing barriers in access to care.

Key facts

NIH application ID
10523407
Project number
2P50HD093074-06
Recipient
DUKE UNIVERSITY
Principal Investigator
Geraldine Dawson
Activity code
P50
Funding institute
NIH
Fiscal year
2022
Award amount
$43,378
Award type
2
Project period
2017-09-07 → 2027-08-31