2018
DOI: 10.1007/s41252-018-0063-7
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Topography and Function of Challenging Behaviors in Individuals with Autism Spectrum Disorder

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Cited by 24 publications
(14 citation statements)
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“…Individuals with autism spectrum disorder (ASD) often demonstrate a variety of disruptive behaviors, which pose an increased risk to their physical health, and social and emotional wellbeing (Hong, Dixon, Stevens, Burns, & Linstead, 2018;Horner, Carr, Strain, Todd, & Reed, 2002). A wide body of research exists on the treatment of many of these disruptive behaviors using differential reinforcement of other behavior (DRO) procedures (e.g., Jessel & Ingvarsson, 2016;Weston, Hodges, & Davis, 2017).…”
mentioning
confidence: 99%
“…Individuals with autism spectrum disorder (ASD) often demonstrate a variety of disruptive behaviors, which pose an increased risk to their physical health, and social and emotional wellbeing (Hong, Dixon, Stevens, Burns, & Linstead, 2018;Horner, Carr, Strain, Todd, & Reed, 2002). A wide body of research exists on the treatment of many of these disruptive behaviors using differential reinforcement of other behavior (DRO) procedures (e.g., Jessel & Ingvarsson, 2016;Weston, Hodges, & Davis, 2017).…”
mentioning
confidence: 99%
“…Previous analysis of the topography of challenging behaviors have manifested as largely qualitative in nature [3]. These studies e↵ectively underline the di culty as well as the necessity of the consistent and reliable labeling of challenging behaviors exhibited by individuals with ASD.…”
Section: Chapter 4 Resultsmentioning
confidence: 98%
“…These studies e↵ectively underline the di culty as well as the necessity of the consistent and reliable labeling of challenging behaviors exhibited by individuals with ASD. In this labeling, one must distinguish between behaviors which, at times, can only be separated based on the implied function of these actions as is the case with Disruptions and Tantrums [3]. In this thesis we look to diverge from a qualitative analysis into the quantitative, allowing for the discovery of patterns and features in behavioral data that could only be extracted through machine learning algorithms.…”
Section: Chapter 4 Resultsmentioning
confidence: 99%
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