Adaptive Functioning and Autism Spectrum Disorder Symptom Severity in Childhood: Parent Perception vs Clinician Rating

Autism Spectrum Disorder (ASD) is a neurocognitive developmental disorder that impacts over one percent of the population. As of 2016, one in 64 children were diagnosed with ASD by four years of age, with males receiving the diagnosis 3.5 times more often than females (Shaw et al. 2020). Research also indicates that ASD prevalence varies by socioeconomic status (SES) and race/ethnicity (Diguiseppi et al., 2016). These differences may be a result of differential access to resources, a connection between SES and race/ethnicity, measure sensitivity to child sex, cultural differences in sensitivity to symptomatology, or a true difference in ASD presentation. Some of the most commonly used tools in assessing children for ASD are parent report forms or clinical interviews with the child’s parent (such as the Vineland Adaptive Behavior Scales, Second Edition; VABS-II) and clinician assessment and observation, frequently using the Autism Diagnostic Observation Schedule, Second Edition (ADOS-2; Gadow et al., 2016). Effectively interpreting parent ratings of their child’s ASD symptom severity can make a difference in how a clinician diagnoses a child and, in turn, what steps are taken to help the child moving forward. The purpose of this dissertation is to examine the association between parent and clinician ratings of a child’s ASD symptomatology. Utilizing two commonly used assessment measures, the VABS-II and the ADOS-2, the association between parent ratings of adaptive functioning and clinician ratings of ASD symptom severity were analyzed. A logistic regression, linear regression, and receiver operating characteristic (ROC) curve were estimated to evaluate the association and the predictive power of the VABS-II for ASD diagnosis based on the ADOS-2. Findings suggested that the VABS-II Adaptive Behavior Composite and the ADOS-2 are inversely related, as hypothesized, but that the association is not moderated by demographic factors. Additionally, the ROC curve showed that the VABS-II can be used to predict ASD diagnosis based on ADOS-2 cut-off scores. These findings and their implications are further discussed in the dissertation