Abstract
This study explored the features of an online program that were effective for parents of children with autism without an intellectual disability. The findings offer preliminary support that e-learning helps parents understand strategies that are important to them because they can improve daily life.
Primary Author and Speaker: Katie Alexander
Additional Authors and Speakers: Winnie Dunn
Contributing Authors: Melissa DeRosier, Debra Childress, Lauren Kenworthy, Laura Anthony, Lynn Cannon, Monica Adler Werner
The literature highlights the importance and value of parent-focused, low-cost, and accessible interventions that improve outcomes for parents and their children. Online tools could meet these requirements, but there is a paucity of currently available, evidence-based programs. To address this gap, an ongoing study aims to develop and test e-Unstuck, an e-learning intervention based on Unstuck and On Target (UOT; Kenworthy et al., 2014), a research-validated program developed for children with ASD without an intellectual disability (ID). The data from the e-Unstuck Phase I feasibility trial provide an opportunity to explore what features of an online program are effective for parents of children with ASD without an ID. Understanding how to support e-learning for parents is important for occupational therapy practitioners, who are well positioned to contribute to the development of interventions that improve outcomes for children with ASD and their parents.
An online survey from the original trial was the source of deidentified data for the current study. The survey included 68 items divided into 45 quantitative and 18 qualitative questions. Together, these items prompted participant feedback on their experiences with and perspectives on all aspects of the UOT e-prototype, including the quality, relevance, and value of content; graphics and animations; the video narrator; interactives and exercises; and the executive function report. To analyze these data, we used convergent parallel mixed methods, a mixed methods strategy that separately analyzes both quantitative and qualitative data and then compares those analyses for divergence and convergence to integrate findings.
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