Toward the development of SMART communication technology: Automating the analysis of communicative trouble and repair in dementia

Background and Objectives Communication difficulties have been reported as one of the most stress-inducing aspects of caring for people with dementia. Notably, with disease progression comes an increase in the frequency of communication difficulty and a reduction in the effectiveness of attempts to remedy breakdowns in communication. The aim of the current research was to evaluate the utility of an automated discourse analysis tool (i.e., Discursis) in distinguishing between different types of trouble and repair signaling behaviors, demonstrated within conversations between people with dementia and their professional care staff. Research Design and Methods Twenty conversations between people with dementia and their professional care staff were human-coded for instances of interactive/noninteractive trouble and typical/facilitative repair behaviors. Associations were then examined between these behaviors and recurrence metrics generated by Discursis. Results Significant associations were identified between Discursis metrics, trouble-indicating, and repair behaviors. Discussion and Implications These results suggest that discourse analysis software is capable of discriminating between different types of trouble and repair signaling behavior, on the basis of term recurrence calculated across speaker turns. The subsequent recurrence metrics generated by Discursis offer a means of automating the analysis of episodes of conversational trouble and repair. This achievement represents the first step toward the future development of an intelligent assistant that can analyze conversations in real time and offers support to people with dementia and their carers during periods of communicative trouble.