Autism Secondary Data Analysis Program - Autism and Attention-Deficit/Hyperactivity Disorder (ADHD) frequently co-occur, with lifetime estimates that approximately 40% of autistic people also have ADHD. This combined profile is associated with diagnostic delays in diagnosis, poorer intervention response, and worse mental and physical health outcomes compared to either condition alone. Despite these challenges, research on factors influencing dual diagnosis remains limited, in part due to historical diagnostic restrictions that did not recognize Autism and ADHD as co-occurring conditions until the DSM-5 was published in 2013. Primary care providers and other community clinicians are often the first point of contact for those seeking diagnostic clarification and supports. Yet, complex cases are often referred to autism specialists for differential diagnosis of Autism and ADHD, which introduces additional accessibility concerns due to long wait lists and high costs that further delay access to appropriate care. These barriers are especially pronounced for females, who are diagnosed with both autism and ADHD at lower rates than males and may present with more nuanced or subtler profiles than males. Barriers are also experienced by individuals with average to above-average cognitive ability who are less likely to be detected or well-understood in community settings. Understanding how evolving diagnostic criteria, provider type, and individual factors (e.g., sex, cognitive ability) impact the likelihood and sequence of autism and ADHD diagnoses is critical to improving identification, reducing disparities, and ensuring timely access to needed supports. This project will examine sex differences in the co-occurrence of Autism and ADHD (AUT+ADHD) using two complementary datasets: (1) a nationally representative dataset from the National Survey of Children’s Health (NSCH, 2016–2025) and (2) a sample clinically-referred for an autism diagnostic evaluation at UNC TEACCH (2000–2025). In both samples, this study will assess how diagnostic criteria, sex, and cognitive ability influence co-occurrence rates. A subsequent, more detailed examination within the TEACCH dataset will provide insights into sex and cognitive differences in diagnostic sequencing, hypothesizing that females and those without intellectual disability will be more likely to receive an ADHD diagnosis prior to autism. To achieve these goals, Aim 1 will use NSCH data to analyze national trends in AUT+ADHD, investigating sex differences in temporal changes in co-occurrence rates across DSM revisions, the influence of provider type, and the impact of cognitive ability. Aim 2 will leverage UNC TEACCH data to determine whether these patterns are replicated or differ in a clinically referred sample, where autism evaluations are the primary reason for assessment. This comparison offers additional insight into whether autism-specific clinical assessments lead to earlier recognition of either diagnosis, particularly for females or those with average to above-average cognitive ability. Finally, we will examine the sequence of autism and ADHD diagnoses within the UNC TEACCH data to understand how the presenting characteristics of these conditions influence diagnostic timing and potential diagnostic overshadowing. Findings from this study will inform clinical training, policy initiatives, and behavioral health workforce development to improve autism and ADHD identification, particularly in generalist community settings where many diagnostic questions first arise. Results will be disseminated through peer-reviewed publications, national conferences, and targeted outreach to healthcare providers, policymakers, and families. This project directly aligns with HRSA’s mission to improve behavioral healthcare access by identifying diagnostic disparities and workforce training needs that can be addressed to enhance early detection and supports for Autism and ADHD in diverse populations.
