Journal
SENSORS
Volume 22, Issue 7, Pages -Publisher
MDPI
DOI: 10.3390/s22072625
Keywords
conversational agents; dialogue systems; relational agents; chatbot
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This paper reviews different types of conversational agents used in health care for chronic conditions and examines their underlying communication technology, evaluation measures, and AI methods. The overall acceptance of conversational agents by users for the self-management of their chronic conditions is promising, although there is a lack of reliable evidence to determine the efficacy of AI-enabled conversational agents due to insufficient reporting of technical implementation details.
This paper reviews different types of conversational agents used in health care for chronic conditions, examining their underlying communication technology, evaluation measures, and AI methods. A systematic search was performed in February 2021 on PubMed Medline, EMBASE, PsycINFO, CINAHL, Web of Science, and ACM Digital Library. Studies were included if they focused on consumers, caregivers, or healthcare professionals in the prevention, treatment, or rehabilitation of chronic diseases, involved conversational agents, and tested the system with human users. The search retrieved 1087 articles. Twenty-six studies met the inclusion criteria. Out of 26 conversational agents (CAs), 16 were chatbots, seven were embodied conversational agents (ECA), one was a conversational agent in a robot, and another was a relational agent. One agent was not specified. Based on this review, the overall acceptance of CAs by users for the self-management of their chronic conditions is promising. Users' feedback shows helpfulness, satisfaction, and ease of use in more than half of included studies. Although many users in the studies appear to feel more comfortable with CAs, there is still a lack of reliable and comparable evidence to determine the efficacy of AI-enabled CAs for chronic health conditions due to the insufficient reporting of technical implementation details.
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