Patterns of Psychiatric Comorbidity in a Sample of School-Aged Children with Autism Spectrum Disorder Receiving Community and School Based Mental Health Services

Background: Psychiatric comorbidity in children with autism spectrum disorder (ASD) is common with rates reported at greater than 70% (Leyfer et al, 2006; Simonoff et al., 2008). Given these high rates, publicly-funded community and school-based mental health (MH) programs play a significant role in treating youth with ASD. Understanding common patterns of psychiatric comorbidity in children with ASD served in publicly-funded MH programs is important to implement appropriately tailored interventions.

Objectives: To identify child sociodemographic and clinical characteristics associated with psychiatric comorbidity for children served in publicly-funded MH services.

Methods: Preliminary data are drawn from baseline assessments from an ongoing randomized community effectiveness trial of AIM HI (“An Individualized Mental Health Intervention for ASD”) conducted in publicly-funded community and school-based MH services. AIM HI is a clinical intervention and training model that targets challenging behaviors in children with ASD and designed to be delivered by community MH providers. The current sample includes 103 children (86% boys) ages 5-14 (M = 8.83 years; SD= 2.51) with existing ASD diagnoses (validated by the ADOS-2) and their primary caregivers. Children were drawn from 17 participating publicly-funded community and school-based MH programs, receiving care from 91 therapists. Non-ASD psychiatric diagnoses were assessed using the MINI-KID (Sheehan et al., 1998) that was adapted for use and conducted by six study personnel with primary caregivers. Sociodemographics were assessed via parent-report, social communication skills were assessed via parent-report on the Social Responsiveness Scale (SRS; Constantino & Gruber, 2005), child behavior problems were assessed via parent-report on the Eyberg Child Behavior Inventory Intensity Scale (ECBI; Eyberg & Pincus, 1999), and child cognitive skills were assessed using the Wechsler Abbreviated Scale of Intelligence-II (Wechsler, 2011). Multivariable logistic regression analyses were conducted to identify child sociodemographics and clinical characteristics associated with meeting criteria for a non-ASD disorder. Data were examined by five diagnostic categories: ADHD, ODD, anxiety, mood, and a Tic Disorder. A model was calculated for each diagnostic category.

Results: Approximately 88% of children met criteria for a non-ASD disorder on the MINI-KID. Factors significantly associated with meeting criteria for an Anxiety Disorder included: less severe social communication difficulties (B = -0.14, p < .05) and higher ASD symptom severity (B = 0.23, p < .05) on the SRS. Factors significantly or marginally associated with meeting criteria for ODD included: greater behavior problems on the ECBI (B = 0.16; p < .01) and ADOS-2 classification as Autism Spectrum (vs. Autism) (B = -1.36; p = .06). No child characteristics were associated with meeting criteria for ADHD, a Mood Disorder, or a Tic Disorder. Child age, race/ethnicity, gender, or cognitive abilities were not associated with any disorder.

Conclusions: The majority of children with ASD receiving publically-funded MH care in this sample met criteria for at least one additional psychiatric condition. Child clinical characteristics were associated with meeting criteria for an Anxiety Disorder and ODD. Results suggest that child clinical correlates may facilitate differential diagnosis and inform appropriate tailoring of intervention for youth with ASD served in general child MH settings.