Although research shows early intensive behavioral intervention is efficacious when delivered in university or private intervention centers, little is known about effectiveness or feasibility of disseminating early intensive behavioral intervention to larger communities. The Michigan State University Early Learning Institute was developed to address gaps in distribution of early intensive behavioral intervention to community settings, with an emphasis of serving children and families on Medicaid. This short report describes the Early Learning Institute’s approach and preliminary utilization data among Medicaid families. Results suggest the model has potential for dissemination within community settings and promote utilization among Medicaid children. Lay abstract Although research shows early intensive behavioral intervention can be very beneficial for children with autism spectrum disorder when delivered in university or private intervention centers, little is known about the best way to provide early intensive behavioral intervention within the broader community. The Michigan State University Early Learning Institute was developed to address challenges with providing early intensive behavioral intervention in community settings, with an emphasis on serving children and families on Medicaid. This short report describes the approach taken by the Early Learning Institute and reports data regarding enrollment and utilization among Medicaid families. Results suggest the model has potential to be used within community settings and that children on Medicaid are likely to consistently attend their treatment sessions.
Applied behavior analysis (ABA) involves the study of human behavior and typically uses human data collectors to observe and measure behavior. Recent developments in technology have introduced various automated data-collection apparatuses that can measure human behavioral data useful to applied behavior-analysts. However, there have been very little extant literature on the use of automated data-collections in applied behavior-analytic research. The current review investigated the extent to which the field of ABA incorporates automated data-collection from selected ABA journals between 2010 to 2019. Of the 2,155 data-based articles selected for the current review, 9.74% (n = 207) used automated data-collection. Among these, 48.31% (n = 100) were coded as being applied research. Limitations and future research for automated data-collection in ABA are also discussed.
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