Predictors of School Refusal Due to Bullying: The Role of ASD + ADHD Co-Occurrence

Background: Children with Autism Spectrum Disorder (ASD) experience bullying victimization more frequently than children without ASD (Maïano et al., 2016). This disparity is concerning as victimization is related to physiological distress, internalizing symptoms, and school refusal (Bitsika & Sharpley, 2014; Havik et al., 2014, 2015; Tipton-Fisler et al., 2018). Predictors of victimization vulnerability include: externalizing/conduct behaviors, older age, non-Caucasian race, co-occurring diagnosis of Attention-Deficit/Hyperactivity Disorder (ADHD), and public school/general education classroom placement (Fink et al., 2018; Sreckovic et al., 2014). However, the relation of victimization predictors and negative outcomes is unknown. Understanding predictors of negative responses to bullying may elucidate characteristics of particularly vulnerable children.

Objectives: Identify predictors of school refusal due to bullying.

Methods: Participants were 97 parents of 154 children (4-16 years old). Children were diagnosed with ASD (n=36), ADHD (n=16), ASD + ADHD (n=31), other diagnoses (n=15), or no diagnosis (n=56). Parents were asked if their child had ever resisted going to school due to being bullied and how frequently this resistance had occurred (i.e., at least once per month, past school year, in the past but not this school year, never). Parents of children with ASD also completed the Autism Spectrum Quotient: Children’s Version (AQ-Child; Auyeung et al., 2008) as a measure of ASD symptom severity. Study participation occurred online.

Results: Parents reported 35% of children had resisted attending school due to bullying. Of these, 63% had resisted within the past school year. Binary logistic regression was conducted to determine the impact of hypothesized predictors (i.e., age, gender, race, diagnosis, attending public school, general education placement, having a behavior plan) on school refusal likelihood. This model was significant, χ2(10) = 35.44, p < .001; it explained 28.4% of variance in school refusal and correctly classified 73.2% of cases. Greater likelihood of school refusal was predicted for children with co-occurring diagnoses of ASD + ADHD (Odds Ratio (OR) 6.6, 95% CI 2.1 to 20.6, p < .01) and children of older age (OR 1.16, 95% CI 1.0 to 1.3, p < .01; see Table 1). Within ASD, symptom severity (AQ-Child) did not predict school refusal (OR 0.97, 95% CI 0.90 to 1.04, ns).

Variables that predicted school refusal with at least trend-level significance were analyzed using ordinal logistic regression for school refusal frequency. The model with these predictors was a significant improvement over the intercept-only model (χ2(8) = 33.51, p<.001). Compared to ASD, diagnoses of ADHD or co-occurring ASD + ADHD predicted more frequent school refusal (OR 4.53 and 5.45, respectively). Older child age and having a behavior plan also predicted more frequent school refusal (see Table 2).

Conclusions: Older children with ASD + ADHD and behavior difficulties may have particular difficulty managing victimization and should be targeted for bullying intervention efforts. In contrast to research on victimization predictors, environmental factors (public school, general education placement) did not predict school refusal. Future research should characterize children with ASD who are bullied and display less severe negative outcomes. These children may possess skills that should be intervention targets.