Diagnostic Challenges in Evaluating Comorbid ADHD in Young Children with ASD

Background: Although co-occurrence of Attention-Deficit/Hyperactivity Disorder (ADHD) and Autism Spectrum Disorder (ASD) symptoms has long been described, comorbid diagnosis of these conditions has only been permitted since publication of the DSM-5. Current estimates suggest ADHD occurs in 20-70% of cases of ASD (Matson et al., 2013), with this broad prevalence range likely associated with different diagnostic methods. Accurate methods of diagnosing these comorbid conditions are needed to clarify prevalence rates and inform research on treatment for the ASD+ADHD phenotype. To date, however, few guidelines exist for the clinical evaluation of this comorbidity.

Objectives: Despite distinct sets of diagnostic criteria, clinicians encounter a number of challenges when evaluating comorbid ADHD and ASD. The current study aims to explore these specific diagnostic challenges and to identify their impact on the diagnostic process and outcomes.

Methods: The Duke NIH Autism Center of Excellence research program aims to improve understanding of the onset, developmental course, and treatment of comorbid ADHD and ASD in young children. Participants complete comprehensive evaluations including gold-standard assessment tools for ASD (i.e., ADI-R, ADOS) and ADHD (ADHD Rating Scale, semi-structured psychiatric clinical interviews) and cognitive (Mullen, DAS-II) and adaptive behavior (Vineland 3) assessments. Historical response to school-based and ASD-focused interventions also informs the diagnostic process. Case review and consensus discussions by clinical psychologists and psychiatrists with expertise in ADHD and ASD are conducted to finalize diagnostic conclusions. Finally, ratings are assigned to each diagnosis to quantify diagnostic confidence.

Results: Thus far, twenty participants with ASD (mean age=68 months, SD=17 months) have completed a diagnostic evaluation, and six (30%) have received a comorbid ADHD diagnosis. A three-point diagnostic confidence scale was used (range 1-3) with higher ratings indicating more confidence. Mean confidence for ASD diagnosis was 2.85 (SD=0.37); mean confidence for ADHD diagnosis was 2.17 (SD=0.75). Diagnostic challenges fall into two broad categories. One challenge arises when distinguishing specific ADHD symptoms from common ASD behaviors, especially when the ADHD-like behavior improves whenever ASD behavioral supports are provided (e.g., using a visual schedule). For example, parents may report that a child often has “difficulty sustaining attention,” but the child’s sustained attention may actually be exceptional for high interest items. Similarly, parent-report of “fidgety” behavior may be more consistent with observed stereotyped, repetitive movements than typical ADHD-like fidgeting. A second often-noted challenge involves incorporating cognitive ability, including intellectual disability and variability in cognitive and/or language skills, into determination of whether symptom presence is excessive for developmental expectations. For example, parent-report of “difficulty following through on instructions” may be better explained by delayed receptive language skills, whereas “difficulty waiting one’s turn” may be age-appropriate when considering a child’s developmental level.

Conclusions: Identifying comorbid ADHD and ASD is essential for ensuring that affected children have access to effective interventions. Given the diagnostic challenges associated with evaluating these comorbidities, identifying procedures to optimize the diagnostic process is essential for making reliable diagnoses. The current project will contribute essential information to the fields of ADHD and ASD research that will inform future research and clinical endeavors.