Differential Influences of ASD and ADHD Symptom Severity on Adaptive Functioning in Youth with and without ASD

Thursday, May 11, 2017: 5:30 PM-7:00 PM
Golden Gate Ballroom (Marriott Marquis Hotel)
Z. J. Williams1, S. L. Jackson2, M. J. Rolison3, T. C. Day2, K. A. McNaughton1, L. Morett1 and J. McPartland2, (1)Yale Child Study Center, New Haven, CT, (2)Child Study Center, Yale School of Medicine, New Haven, CT, (3)Child Study Center, Yale University School of Medicine, New Haven, CT
Background: Autism Spectrum Disorder (ASD) and Attention-Deficit/Hyperactivity Disorder (ADHD) are highly comorbid conditions, with population-based studies reporting that approximately 20% of children with ASD meet full criteria for an ADHD diagnosis (Surén et al., 2012). Children with comorbid ASD and ADHD tend to exhibit higher levels of autistic traits and lower levels of adaptive functioning than children with ASD alone, ADHD alone, or neither disorder. Only one study to date has investigated the ability of both ASD and ADHD symptom levels to predict adaptive functioning, finding that only ASD symptoms predicted adaptive behavior scores in a group of children with ASD, ADHD, or comorbid ASD/ADHD (Ashwood et al., 2015). It remains unknown whether that same relationship between dimensional trait measures and adaptive functioning exists in children with sub-clinical ASD/ADHD symptoms and higher levels of adaptive behavior.

Objectives: The current study aims to examine the relationship between dimensional measures of ASD and ADHD symptoms and adaptive functioning skills in youth with and without diagnosed ASD.

Methods: Parents of 45 (33 male, 12 female) intellectually able children and adolescents with ASD (age range 8-18, M = 14.13, SD = 2.62) completed the Child Behavior Checklist 6-18 (CBCL), Social Responsiveness Scale-Parent Report (SRS), and Vineland Adaptive Behavior Scales, Second Edition (VABS). These measures were also collected from the parents of 31 (17 male, 14 female) age- and IQ-matched typically developing (TD) controls (mean age = 14.13, SD = 2.24). The SRS total T-score served as a measure of autism symptoms, and the CBCL’s Attention-Deficit Hyperactivity Problems (ADHP) T-score served as a measure of ADHD symptoms. Hierarchical regression analyses were performed separately for the two diagnostic groups, with the VABS subscales and Adaptive Behavior Composite (ABC) as dependent variables, Age, Sex, and FSIQ scores entered as independent variables during the first step (enter-method), and SRS and ADHP T-scores entered as independent variables during the second step of the analyses (stepwise-method).

Results: Regression analysis indicated that lower overall adaptive functioning (i.e. VABS ABC) was significantly predicted by higher SRS T-scores (β=-0.33) in the ASD group and higher ADHP T-scores (β=-0.41) in the TD group. Higher SRS T-scores significantly predicted reduced VABS Communication scores in both the ASD (β=-0.33) and TD (β=-0.49) groups. Like ABC scores, VABS Socialization scores were predicted by SRS T-scores (β=-0.42) in the ASD group and ADHP T-scores (β=-0.37) in the TD group. The regression model did not significantly predict VABS Daily Living Skills scores for either group (ASD: p=0.074; TD: p=0.194). The addition of ASD or ADHD symptom scores resulted in significant improvements in the predictive strength of all other models (ΔR2=0.11–0.22, ps<0.05). In no model did both ASD and ADHD symptom levels independently predict adaptive behavior scores.

Conclusions: While ASD severity predicted overall adaptive functioning in those with ASD, sub-clinical ADHD symptoms more strongly predicted decreased adaptive functioning in children without either disorder. This finding implies that when present at sub-clinical levels, ADHD rather than ASD symptoms are more strongly related to functional impairment in the general population.