Center News

Recent data suggests that the gap in autism diagnosis between Black and white youth has narrowed. In a new open access article in Autism Research, Danai Fannin, PhD, and colleagues question whether this means better access to supports for Black autistic youth. Dr. Fannin is a member of the Duke Autism Center of Excellence Community Engagement Advisory Board and an adjunct faculty member at Duke Head and Neck Surgery & Communication Sciences.

As an advocate, educator, and dedicated clinical care professional, Mary Beth Hooks serves as an esteemed clinician here at the Duke Center for Autism. Mary Beth, originally from a small town in eastern North Carolina called Fremont, moved to the sprawling metropolis of the Triangle in 2004. She received her Bachelor of Arts in Psychology from North Carolina State University (NCSU) in 2008, and continued her education through training in Applied Behavior Analysis, and eventually receiving a Master of Social Work graduate degree from NCSU.

On April 18, 2024, Elena Tenenbaum, PhD, Assistant Professor in Psychiatry and Behavioral Sciences, spoke to the hosts of the WPTF Morning Show about adult autism awareness. Listen to the radio segment here.

On April 3, 2024, Hari Srinivasan presented the keynote address in the Duke Center for Autism and Brain Development's 2023-24 Autism Seminar Series, in recognition of Autism Acceptance Month. 

The article "Developing an inclusive campus for autistic students" appears in the March 2024 issue of the Journal of Diversity in Higher Education. The paper discusses specific ways that colleges can become more accessible for autistic students.

Dr. Geraldine Dawson is quoted in this blog post from IEP resource website A Day in Our Shoes with Lisa Lightner.

Dr. Geraldine Dawson is interviewed on the ABCs of Disability Planning podcast about novel digital health approaches for autism screening and outcome monitoring.

Dr. Dawson is interviewed on the European Medical Journal Reviews podcast in a two-part episode.

Duke AI Health Fellow In the United States, one in 36 children is diagnosed with autism. Early detection of autism ensures timely access to intervention, and accurate screening is a critical first step to diagnosis and linkage to early services. Sophisticated computational tools, such as machine learning models, may increase autism screening accuracy and help reduce disparities in access to diagnosis and intervention.