TY - JOUR
T1 - A Systematic Review on Healthcare Artificial Intelligent Conversational Agents for Chronic Conditions
AU - Sawad, Abdullah Bin
AU - Narayan, Bhuva
AU - Alnefaie, Ahlam
AU - Maqbool, Ashwaq
AU - McKie, Indra
AU - Smith, Jemma
AU - Yuksel, Berkan
AU - Puthal, Deepak
AU - Prasad, Mukesh
AU - Kocaballi, A. Baki
N1 - Funding Information:
Vik chatbot helpful and supported by 88% (943/958).
Publisher Copyright:
© 2022 by the authors. Licensee MDPI, Basel, Switzerland.
PY - 2022/4/1
Y1 - 2022/4/1
N2 - 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.
AB - 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.
KW - chatbot
KW - conversational agents
KW - dialogue systems
KW - relational agents
UR - http://www.scopus.com/inward/record.url?scp=85127207395&partnerID=8YFLogxK
U2 - 10.3390/s22072625
DO - 10.3390/s22072625
M3 - Review article
C2 - 35408238
AN - SCOPUS:85127207395
SN - 1424-8220
VL - 22
JO - Sensors (Switzerland)
JF - Sensors (Switzerland)
IS - 7
M1 - 2625
ER -