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Updated: Nov 1, 2025

A Familiarization Protocol Facilitates the Participation of Children with ASD in Electrophysiological Research
Published on: July 31, 2017
Parent perceived challenges to treatment utilization in a publicly funded early intensive behavioral intervention
Marissa E Yingling1, Robert M Hock2, Amy P Cohen3
1College of Behavioral, Social, and Health Sciences, Clemson University, Clemson, SC, USA.
Abstract:
Background: In recent years, the delivery of early intensive behavioral intervention (EIBI) for children with autism spectrum disorder (ASD) in the United States has significantly changed. More children with ASD than ever before are eligible to use publicly funded EIBI. Yet, the challenges to large-scale implementation of EIBI remain unclear. Specific Aims: We examined parent perceived challenges to treatment utilization, predictors of increased challenges to treatment utilization, and parent recommendations for increasing utilization in a statewide EIBI program. Method: Using a cross-sectional design, we surveyed parents of children with ASD receiving EIBI through South Carolina's Pervasive Developmental Disorder Program (N = 145). To examine the contributions of parent demographic characteristics, parent social support, and child challenging behaviors to perceived challenges to utilization, we used multiple linear regression. Parent recommendations were collected using a single open-ended question. Findings: The most frequently endorsed challenges included the child's school schedule (62.1%) and the child being overburdened with other treatment demands (65.2%). Greater child challenging behaviors were associated with a greater degree of perceived challenges, and social support was associated with a lesser degree of perceived challenges. Discussion: Parents perceived various challenges to utilization, and child and family characteristics may increase the risk for experiencing challenges to utilization. As the delivery of EIBI continues to evolve in the United States and elsewhere, these findings have implications for policy, programming, and future research.
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