The prevalence of developmental delays that make children eligible for Part C services is much higher than previously thought. Moreover, the majority of children who are eligible for Part C services are not receiving services for their developmental problems. Strategies need to be developed to monitor patterns of enrollment in early intervention services and reach out to more minority children, particularly black children.

The Study to Explore Early Development (SEED), a multisite investigation addressing knowledge gaps in autism phenotype and etiology, aims to: (1) characterize the autism behavioral phenotype and associated developmental, medical, and behavioral conditions and (2) investigate genetic and environmental risks with emphasis on immunologic, hormonal, gastrointestinal, and sociodemographic characteristics. SEED uses a case–control design with population-based ascertainment of children aged 2–5 years with an autism spectrum disorder (ASD) and children in two control groups—one from the general population and one with non-ASD developmental problems. Data from parent-completed questionnaires, interviews, clinical evaluations, biospecimen sampling, and medical record abstraction focus on the prenatal and early postnatal periods. SEED is a valuable resource for testing hypotheses regarding ASD characteristics and causes.

The Study to Explore Early Development (SEED) is a multi-site case–control study designed to explore the relationship between autism spectrum disorder (ASD) phenotypes and etiologies. The goals of this paper are to (1) describe the SEED algorithm that uses the Autism Diagnostic Interview-Revised (ADI-R) and Autism Diagnostic Observation Schedule (ADOS) to classify children with ASD, (2) examine psychometric properties of different ASD classification methods, including the SEED method that incorporates rules for resolving ADI-R and ADOS discordance, and (3) determine whether restricted interests and repetitive behaviors were noted for children who had instrument discordance resolved using ADI-R social and communication scores. Results support the utility of SEED criteria when well-defined groups of children are an important clinical or research outcome.

This research documented substantial variability in the proportion of children who are likely to be eligible for Part C services. Most states have adopted eligibility definitions that make many more children candidates for Part C early intervention than they serve. However, current rates of enrollment are insufficient to serve all children with delays that fall under 2 SDs below the mean on any of the 5 developmental domains that are required to be evaluated by Part C regulations.

Self-injurious behaviors (SIB) have been reported in more than 30 % of children with an autism spectrum disorder (ASD) in clinic-based studies. This study estimated the prevalence of SIB in a large population-based sample of children with ASD in the United States. A total of 8065 children who met the surveillance case definition for ASD in the Autism and Developmental Disabilities Monitoring (ADDM) Network during the 2000, 2006, and 2008 surveillance years were included. The presence of SIB was reported from available health and/or educational records by an expert clinician in ADDM Network. SIB prevalence averaged 27.7 % across all sites and surveillance years, with some variation between sites. Clinicians should inquire about SIB during assessments of children with ASD.

The Social Communication Questionnaire (SCQ) and the Social Responsiveness Scales (SRS) are commonly used screeners for autism spectrum disorder (ASD). Data from the Study to Explore Early Development were used to examine variations in the performance of these instruments by child characteristics and family demographics. For both instruments, specificity decreased as maternal education and family income decreased. Specificity was decreased with lower developmental functioning and higher behavior problems. This suggests that the false positive rates of the SRS and the SCQ are associated with child characteristics and family demographic factors. There is a need for ASD screeners that perform well across socioeconomic and child characteristics. Clinicians should be mindful of differential performance of these instruments in various groups of children.

Background The Study to Explore Early Development (SEED) is designed to enhance knowledge of autism spectrum disorder characteristics and etiologies. Objective This paper describes the demographic profile of enrolled families and examines sociodemographic differences between children with autism spectrum disorder and children with other developmental problems or who are typically developing. Methods This multi-site case-control study used health, education, and birth certificate records to identify and enroll children aged 2–5 years into one of three groups: 1) cases (children with autism spectrum disorder), 2) developmental delay or disorder controls, or 3) general population controls. Study group classification was based on sampling source, prior diagnoses, and study screening tests and developmental evaluations. The child's primary caregiver provided demographic characteristics through a telephone (or occasionally face-to-face) interview. Groups were compared using ANOVA, chi-squared test, or multinomial logistic regression as appropriate. Results Of 2768 study children, sizeable proportions were born to mothers of non-White race (31.7%), Hispanic ethnicity (11.4%), and foreign birth (17.6%); 33.0% of households had incomes below the US median. The autism spectrum disorder and population control groups differed significantly on nearly all sociodemographic parameters. In contrast, the autism spectrum disorder and developmental delay or disorder groups had generally similar sociodemographic characteristics. Conclusions SEED enrolled a sociodemographically diverse sample, which will allow further, in-depth exploration of sociodemographic differences between study groups and provide novel opportunities to explore sociodemographic influences on etiologic risk factor associations with autism spectrum disorder and phenotypic subtypes.

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