Duke Center for Autism and Brain Development 2021 Impact Report

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Research

Innovative Digital Solutions Aim to Improve Screening and Diagnosis, Reduce Healthcare Disparities Early identification of autism is key, but the journey to diagnosis is not equal for everyone.

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or many families, the road from initial concern to evaluation to autism diagnosis can be confusing, slow, and riddled with delays. Approved screening tools, although effective, are subjective measures, partially reliant upon caregiver questionnaires that have been shown to underperform with people of color, those with literacy barriers, and those who have lower educational backgrounds. Once a referral is made, a trained child development expert conducts a diagnostic assessment relying on observations of the child’s behavior during semi-standardized behavioral tasks. Access to licensed diagnosticians can be extremely limited, and in many rural and low-resource areas—including in the United States—there are no licensed providers.

Duke Center for Autism and Brain Development investigators are working to reduce these disparities with digital, accessible, and userfriendly autism detection tools that improve screening techniques, open doors to access in low-resource communities, and help doctors track children’s progress. “Today the playing field is not level. Those who gain easier access to screening tools and clinical diagnosis get the jump on evidence-based interventions and the benefits they bring,” said Duke Center for Autism Director Geraldine Dawson, Ph.D. “With creative, cross-disciplinary research, we can find innovative solutions that bring about equal access and reduce healthcare disparities.”

A digital health approach to autism screening eye gaze facial landmarks expression social communication head turn/response to name

Child watches strategically designed brief movies on a smartphone or tablet

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Duke Center for Autism and Brain Development

Child’s responses to the movies are recorded and automatically quantified via computer vision analysis.

Machine learning uses multiple behaviors to create an objective screening algorithm.


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