PREDICTING AUTISM SPECTRUM DISORDER (ASD) SYMPTOM SEVERITY FROM ACCESS TO SERVICES

Abstract

Children who suffer from Autism Spectrum Disorders (ASD) present with varying severity of core deficits in communication, social skills, and the presence of stereotypic and restrictive behaviors (American Psychiatric Association, 2000). Symptoms emerge early in life, but advancements in screening and diagnostics have enabled clinicians to accurately identify children with ASD within the first two years of life (Zwaigenbaum et al., 2009). The process of early identification is an important one as early interventions services are associated with positive outcomes. These services are most likely to be the responsibility of the public school system to provide (Kasari, Freeman, & Paparella, 2006). However, school-based services have not proven to be effective (Bellini, Peters, Benner, & Hopf, 2007). As a result, children with ASD are more likely to experience unmet behavioral healthcare needs and have difficulty accessing behavioral health services (Chiri & Warfield, 2012). This study aims to explore the relationship between ASD symptom severity and access to behavioral healthcare services. Specifically, we investigated the extent to which ASD symptom severity was predicted by lack of adequate health insurance coverage, lack of school resources, and age of diagnosis. The degree to which these variables were associated with ASD symptom severity beyond the contributions of ethnicity, (SES), and highest parent education level was explored. Results indicated poor fit with the hypothesized model(, [chi]2(7, N = 229) = 6.2 p < .517) with only 8% of the variance explained. Although these results failed to produce a significant finding, this paper highlights a need to identify predictors of ASD symptom severity.