Effectiveness of conversational agents (virtual assistants) in healthcare: protocol for a systematic review
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Author(s)
Type
Journal Article
Abstract
Background:
Conversational agents have evolved in recent decades to become multimodal, multifunctional platforms that have the potential to automate a diverse range of health-related activities, supporting the general public, patients and physicians. Multiple studies have reported the development of these agents and recent systematic reviews have described the scope of use of conversational agents in healthcare. However, there is little focus on the effectiveness of these systems, thus the viability and applicability of these systems is unclear.
Objective:
The objective of this systematic review is to assess the effectiveness of conversational agents in healthcare and to identify limitations, adverse events and areas for future investigation of these agents.
Methods:
The Preferred Reporting Items for Systematic Reviews and Meta-Analyses Protocols will be used to structure this protocol. The focus of the systematic review is guided by a population, intervention, comparator, and outcome framework . A systematic search of PubMed (Medline), EMBASE, CINAHL, and Web of Science will be conducted. Two authors will independently screen the titles and abstracts of identified references and select studies according to the eligibility criteria. Any discrepancies will then be discussed and resolved. Two reviewers will extract and validate data, respectively, from included studies into a standardised form and conduct quality appraisal.
Results:
At the time of writing, we have begun a preliminary literature search and piloting of the study selection process.
Conclusions:
This systematic review aims to clarify the effectiveness, limitations and future applications of conversational agents in healthcare. Our findings may be used to inform future development of conversational agents and further the personalisation of care.
Conversational agents have evolved in recent decades to become multimodal, multifunctional platforms that have the potential to automate a diverse range of health-related activities, supporting the general public, patients and physicians. Multiple studies have reported the development of these agents and recent systematic reviews have described the scope of use of conversational agents in healthcare. However, there is little focus on the effectiveness of these systems, thus the viability and applicability of these systems is unclear.
Objective:
The objective of this systematic review is to assess the effectiveness of conversational agents in healthcare and to identify limitations, adverse events and areas for future investigation of these agents.
Methods:
The Preferred Reporting Items for Systematic Reviews and Meta-Analyses Protocols will be used to structure this protocol. The focus of the systematic review is guided by a population, intervention, comparator, and outcome framework . A systematic search of PubMed (Medline), EMBASE, CINAHL, and Web of Science will be conducted. Two authors will independently screen the titles and abstracts of identified references and select studies according to the eligibility criteria. Any discrepancies will then be discussed and resolved. Two reviewers will extract and validate data, respectively, from included studies into a standardised form and conduct quality appraisal.
Results:
At the time of writing, we have begun a preliminary literature search and piloting of the study selection process.
Conclusions:
This systematic review aims to clarify the effectiveness, limitations and future applications of conversational agents in healthcare. Our findings may be used to inform future development of conversational agents and further the personalisation of care.
Date Issued
2020-03-09
Date Acceptance
2019-12-16
Citation
JMIR Research Protocols, 2020, 9 (3), pp.1-6
ISSN
1929-0748
Publisher
JMIR Publications
Start Page
1
End Page
6
Journal / Book Title
JMIR Research Protocols
Volume
9
Issue
3
Copyright Statement
©Caroline de Cock, Madison Milne-Ives, Michelle Helena van Velthoven, Abrar Alturkistani, Ching Lam, Edward Meinert.
Originally published in JMIR Research Protocols (http://www.researchprotocols.org), 09.03.2020. This is an open-access article
distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which
permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR
Research Protocols, is properly cited. The complete bibliographic information, a link to the original publication on
http://www.researchprotocols.org, as well as this copyright and license information must be included.
Originally published in JMIR Research Protocols (http://www.researchprotocols.org), 09.03.2020. This is an open-access article
distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which
permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR
Research Protocols, is properly cited. The complete bibliographic information, a link to the original publication on
http://www.researchprotocols.org, as well as this copyright and license information must be included.
Identifier
https://www.researchprotocols.org/2020/3/e16934/
Subjects
Science & Technology
Life Sciences & Biomedicine
Health Care Sciences & Services
conversational agent
chatbot
voice recognition software
speech recognition software
artificial intelligence
virtual health care
avatar
virtual assistant
virtual nursing
virtual coach
intelligent assistant
digital health
artificial intelligence
avatar
chatbot
conversational agent
digital health
intelligent assistant
speech recognition software
virtual assistant
virtual coach
virtual health care
virtual nursing
voice recognition software
1103 Clinical Sciences
1117 Public Health and Health Services
Publication Status
Published
Date Publish Online
2020-03-09