(SDAS) Autism Intervention Challenges for Low-Income Children
Project Number: R40 MC 22642-01 Grantee: Regents of the University of California, Los Angeles Department/Center: Pediatrics / Child Health Policy Project Date: 9/1/2011
Alice Kuo, MD, PhD Associate Professor UCLA Center for Healthier Children, 10990 Wilshire Blvd, Ste 900 Los Angeles, CA 90024-3953 Phone: 310-312-9053 Email: firstname.lastname@example.org
Toddlerhood (1-2 years)
Early Childhood (3-5 years)
Background: Much of the focus of Autism Spectrum Disorder (ASD) research to date has been to determine the characteristics of effective interventions, and some research has begun to look at the effectiveness of these interventions for low-income populations. As the population of young children with ASD grows, desirable outcomes will only be obtained if interventions and services are available to all children with ASD, regardless of socio-economic status.
Objective: This proposed study addresses an important need in the field of ASD research, which is to identify the challenges to accessing ASD interventions and services that children with ASD from underserved families are facing.
Methods: For this study, we will utilize the MCHB-funded Autism Intervention Research
Network on Behavioral Health (AIR-B), which recruits children with autism from five study
sites: UCLA, University of Michigan, Kennedy Krieger Institute, Florida State University and
the University of Washington. A total of 160 young children with ASD will be enrolled in their
study, and data were collected on sociodemographic variables, caregiver relationship, parental stress, parental expectations, ASD services and interventions and child language outcomes.
Analysis: Univariate, bivariate, and regression analyses will be performed. Bivariate
relationships between the dependent variables (ASD intervention and services and child
language outcomes) and each independent variable (including sociodemographic, caregiver
relationship, parental stress, and parental expectation characteristics) will be analyzed. Variables that are significant (p<0.05) in bivariate analyses will be included in a multivariate analyses.
Multivariate regression analyses will be conducted to examine the predictors leading to greater completion of intervention and greater language outcomes for underserved and under-resourced children with ASD. All analyses will control for socio-economic status and race/ethnicity of the target child's family.
Significance: As more effective interventions have been developed for children with ASD,
identifying these children as early as possible is a priority. Race/ethnicity and socioeconomic
status may affect the timely diagnosis of ASD, and recent studies suggest possible disparities in the diagnosis of ASD in these populations. Because early detection and timely initiation of ASD therapy are essential components of successful therapy, ethnic barriers to access to ASD services and interventions have potentially profound implications for the children and families involved.
Access to Health Care, Autism, Early Intervention, Developmental Disabilities,
Health Disparities, Parent-Child Relationship, Special Health Care Needs, Stress, Cognitive & Linguistic Development