Creative Commons License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.
Date of Graduation
Master of Arts (MA)
Department of Graduate Psychology
Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder whose defining characteristics include deficits in social communication and restricted, repetitive patterns of behavior, interests, and/or activities (Weiss, Baker, & Butter, 2016). Children diagnosed with ASD frequently engage in disruptive and destructive behaviors that have the function of escaping from work demands. These behaviors impact their ability to contact important instructional material, further impacting their levels of independence. Practitioners typically intervene on these behaviors using interventions that rely heavily on consequence-based interventions. Although there is an abundance of research on effective consequence-based interventions to treat these behaviors, these interventions are often difficult to implement and may carry risks that impede their usage in a wide variety of settings including schools. Research has demonstrated that antecedent based interventions, such as high-probability command sequences and an antecedent prompting error correction procedure, can be effective for creating behavior change.
This study utilized an AB research design to evaluate the effects of an antecedent prompting error correction intervention on the escape maintained disruptive behaviors and compliance with low probability in a child diagnosed with ASD. The 2020 COVID-19 pandemic resulted in university shutdowns that ended data collection prematurely. Conclusions about the effectiveness of this intervention were unable to be drawn due to this. Based on the research that was conducted, the primary researcher outlined next steps for future research on this topic.
Knox, Emily, "Analysis of an antecedent prompting error correction on rates of disruptive behaviors and compliance in children diagnosed with autism spectrum disorder" (2020). Masters Theses, 2020-current. 42.
Available for download on Saturday, May 03, 2025