Developing discourse structure analysis for use on conversations that include people with aphasia

Autor: Gulick, Eleanor
Jazyk: angličtina
Rok vydání: 2020
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Druh dokumentu: Text
Popis: Conversation based group therapy for people with aphasia (PWA) has been shown to be an efficacious treatment approach benefitting participants’ communication abilities and quality of life. However, little is known regarding the practices facilitators should follow to best support the process of communication rehabilitation. Researchers interested in studying this treatment approach face limitations due to the available methodologies. The current study aimed to fill this gap by beginning to expand the established Discourse Structure Analysis speech function network developed for investigation of casual conversation for use on conversations including PWA. This study focused on repair sequences, given the ubiquity of this type of segment in group conversation therapy. Further, this study oriented towards providing preliminary information about the reliability of the novel repair-focused coding framework. During the first phase, video recordings of four group therapy sessions were analyzed to operationalize a comprehensive class of speech functions that represent the behaviors enacted in sequences that orient to understanding ambiguous productions by PWA. This formed the repair speech function class. Next, two student research assistants were trained to apply the repair speech function framework to excerpts from group conversation therapy. Through the iterative and collaborative process employed in this study, 17 novel speech functions were operationalized. Inter-rater reliability of trained coders applying the repair speech function class was variable across coders but generally showed substantial agreement. The results of this study suggest that the development of a comprehensive network to systematically study group therapy sessions is feasible, though continued research is needed to explicate an optimal framework.
Databáze: Networked Digital Library of Theses & Dissertations