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

> **NIH NIH P50** · DUKE UNIVERSITY · 2024 · $801,807

## 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:** 10909162
- **Project number:** 5P50HD093074-08
- **Recipient organization:** DUKE UNIVERSITY
- **Principal Investigator:** Geraldine Dawson
- **Activity code:** P50 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $801,807
- **Award type:** 5
- **Project period:** 2017-09-07 → 2027-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10909162

## Citation

> US National Institutes of Health, RePORTER application 10909162, A digital health approach to early identification and outcome monitoring in autism (5P50HD093074-08). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/10909162. Licensed CC0.

---

*[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*