A Systematic Review on Healthcare Artificial Intelligent Conversational Agents for Chronic Conditions

Abdullah Bin Sawad; Bhuva Narayan; Ahlam Alnefaie; Ashwaq Maqbool; Indra Mckie; Jemma Smith; Berkan Yuksel; Deepak Puthal; Mukesh Prasad; A. Baki Kocaballi

doi:10.3390/s22072625

Sensors (Mar 2022)

A Systematic Review on Healthcare Artificial Intelligent Conversational Agents for Chronic Conditions

Abdullah Bin Sawad,
Bhuva Narayan,
Ahlam Alnefaie,
Ashwaq Maqbool,
Indra Mckie,
Jemma Smith,
Berkan Yuksel,
Deepak Puthal,
Mukesh Prasad,
A. Baki Kocaballi

Affiliations

Abdullah Bin Sawad: School of Computer Science, Faculty of Engineering and IT, University of Technology Sydney, Sydney 2007, Australia
Bhuva Narayan: School of Communication, Faculty of Arts and Social Sciences, University of Technology Sydney, Sydney 2007, Australia
Ahlam Alnefaie: School of Computer Science, Faculty of Engineering and IT, University of Technology Sydney, Sydney 2007, Australia
Ashwaq Maqbool: School of Public Health, Faculty of Medicine and Health, The University of Sydney, Sydney 2007, Australia
Indra Mckie: School of Communication, Faculty of Arts and Social Sciences, University of Technology Sydney, Sydney 2007, Australia
Jemma Smith: School of Biomedical Engineering, Faculty of Engineering and IT, University of Technology Sydney, Sydney 2007, Australia
Berkan Yuksel: School of Computer Science, Faculty of Engineering and IT, University of Technology Sydney, Sydney 2007, Australia
Deepak Puthal: Department of Electrical Engineering and Computer Science, Khalifa University, Abu Dhabi P.O. Box 127788, United Arab Emirates
Mukesh Prasad: School of Computer Science, Faculty of Engineering and IT, University of Technology Sydney, Sydney 2007, Australia
A. Baki Kocaballi: School of Computer Science, Faculty of Engineering and IT, University of Technology Sydney, Sydney 2007, Australia

DOI: https://doi.org/10.3390/s22072625
Journal volume & issue: Vol. 22, no. 7
p. 2625

Abstract

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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.

Published in Sensors

ISSN: 1424-8220 (Online)
Publisher: MDPI AG
Country of publisher: Switzerland
LCC subjects: Technology: Chemical technology
Website: http://www.mdpi.com/journal/sensors

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