Factors That Drive Access to Services for Children with Neurodevelopmental Disorders in Low Income Populations

Background:  Children with Autism Spectrum Disorder (ASD) and Attention Deficit Hyperactivity Disorder (ADHD) from low-income households are identified later and receive fewer services than children from high-income households. This ‘double whammy’ in diagnosis and treatment means that, throughout their lives, children from low-income populations receive less intervention than children from middle- and high-income populations (Liptak et al., 2008; Thomas et al., 2007). Disparity in access to medical and non-medical services may result from internal and external factors. To address disparities in low-income, and ethnically and racially diverse ASD and ADHD populations, researchers must understand the factors linked to the presence of services.

Objectives:  Identify factors related to services that children with neurodevelopmental disorders receive in school and private settings. Researchers hypothesized: (1) Elevated scores on BRIEF Global Executive Composite (GEC) and CBCL Problems will positively correlate with the presence of both medication and non-medication services. (2) Families of children without services will report more strain and less competence and self-efficacy.

Methods: Participants included 96 children ages 8-11 (M=9.67, SD=.83) from Title I schools (M=$100,727.23, SD=$83,853.08). Participants were referred to a school-based treatment study with a likely diagnosis of ADHD or ASD. Participants were analyzed by service type: (1) Children receiving non-medication services in school and private settings, N=45, (2) Children receiving both medication services and non-medication services, N=24, and (3) Children not receiving any services, N=27. Children only receiving medication were excluded from analyses. Parents completed self-report measures of caregiver strain, family empowerment, and child service programs.

Results: Findings indicate children’s impairments in executive functioning and behavior significantly differ among service type, F(3, 95)=9.429, p<.001. Specifically, children receiving both medication and non-medication services were associated with the highest levels of executive dysfunction and problem behaviors; their families experience significantly greater strain. Children without services show less executive dysfunction and problem behaviors, while their families report less strain. When child behavioral measures were removed from the model, the significance of parental strain in relation to receiving both services persisted (r=.225, p=.040). Families of children without services did not report elevated strain (r=-.216, p=.030). However, absence of services was negatively related to parental self-efficacy (r=-.225, p=.039). When controlling for child behaviors, parental competence was strongly correlated with parental self-efficacy (r=.476, p<.001).

Conclusions: As anticipated, children with greater executive functioning needs and problem behaviors received both medication and non-medication services. Unexpectedly, families of children receiving both services experienced more strain than those who were not receiving services. This finding held true even when child behavioral characteristics were factored out of the relationship. Finally, independent of level of child functioning, parents report low self-efficacy in the absence of services. When parents are not confident in their ability to help their children and do not perceive child difficulties as family strain, children do not receive intervention. This further contributes to disparity in services within the present population. To better understand the relationships that predict services for low-income children with neurodevelopmental disorders, future studies should explore causal relationships that mediate access to services among diverse populations.