Big Data Approach to Characterize Restricted and Repetitive Behaviors in Autism

Abstract

Objective Despite being a core diagnostic feature of autism spectrum disorder (ASD), demographic, developmental and clinical correlates of restricted and repetitive behaviors and interests (RRB) remain poorly characterized. This study aimed to utilize the largest available RRB data set to date to provide a comprehensive characterization of how distinct RRB domains vary according to a range of individual characteristics.Method Data were obtained from 17,581 children and adolescents with ASD (mean age= 8.24 years, SD age= 4.06) from the Simons Foundation Powering Autism Research for Knowledge cohort. Caregivers completed the Repetitive Behavior Scale-Revised questionnaire as a measure of repetitive motor behaviors, self-injurious behaviors, compulsions, insistence on sameness, and circumscribed interests RRB domains. Caregivers also provided information on children's cognitive functioning, language ability, and social and communication impairments.Results Male sex was associated with higher severity of repetitive motor behaviors and restricted interests and with lower severity of compulsions and self-injurious behaviors; no sex differences were found for the insistence on sameness domain. Although repetitive motor behaviors showed a mostly linear (negative) association with age, other RRB domains showed more complex and nonlinear pattern of associations. Higher severity of social and communication impairments provided significant independent contribution in predicting higher severity of all RRB domains at the p < .001 level; however, these effects were small (d < 0.25). The strongest of these effects was observed for insistence on sameness (d = 0.24), followed by repetitive motor behaviors (d = 0.21), compulsions (d = 0.17), restricted interests (d = 0.14), and self-injurious behaviors (d = 0.12).Conclusion Findings reported here provide further evidence that RRB subdomains show a somewhat distinct pattern of associations with demographic, developmental, and clinical variables, with a key implication that separate consideration of these domains can help to facilitate efforts to understand diverse ASD etiology and to inform the design of effective interventions.