Effectiveness of Conversational Agents (Virtual Assistants) in Health Care: Protocol for a Systematic Review
Conversational agents (also known as chatbots) have evolved in recent decades to become multimodal, multifunctional platforms with potential to automate a diverse range of health-related activities supporting the general public, patients, and physicians. Multiple studies have reported the developmen...
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| Published in | JMIR research protocols Vol. 9; no. 3; p. e16934 |
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| Main Authors | , , , , , |
| Format | Journal Article |
| Language | English |
| Published |
Canada
JMIR Publications
09.03.2020
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| Subjects | |
| Online Access | Get full text |
| ISSN | 1929-0748 1929-0748 |
| DOI | 10.2196/16934 |
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| Abstract | Conversational agents (also known as chatbots) have evolved in recent decades to become multimodal, multifunctional platforms with 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 health care. However, there is scarce research on the effectiveness of these systems; thus, their viability and applicability are unclear.
The objective of this systematic review is to assess the effectiveness of conversational agents in health care and to identify limitations, adverse events, and areas for future investigation of these agents.
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 the PubMed (Medline), EMBASE, CINAHL, and Web of Science databases will be conducted. Two authors will independently screen the titles and abstracts of the identified references and select studies according to the eligibility criteria. Any discrepancies will then be discussed and resolved. Two reviewers will independently extract and validate data from the included studies into a standardized form and conduct quality appraisal.
As of January 2020, we have begun a preliminary literature search and piloting of the study selection process.
This systematic review aims to clarify the effectiveness, limitations, and future applications of conversational agents in health care. Our findings may be useful to inform the future development of conversational agents and promote the personalization of patient care.
PRR1-10.2196/16934. |
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| AbstractList | Background: Conversational agents (also known as chatbots) have evolved in recent decades to become multimodal, multifunctional platforms with 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 health care. However, there is scarce research on the effectiveness of these systems; thus, their viability and applicability are unclear. Objective: The objective of this systematic review is to assess the effectiveness of conversational agents in health care 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 the PubMed (Medline), EMBASE, CINAHL, and Web of Science databases will be conducted. Two authors will independently screen the titles and abstracts of the identified references and select studies according to the eligibility criteria. Any discrepancies will then be discussed and resolved. Two reviewers will independently extract and validate data from the included studies into a standardized form and conduct quality appraisal. Results: As of January 2020, 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 health care. Our findings may be useful to inform the future development of conversational agents and promote the personalization of patient care. International Registered Report Identifier (IRRID): PRR1-10.2196/16934 BackgroundConversational agents (also known as chatbots) have evolved in recent decades to become multimodal, multifunctional platforms with 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 health care. However, there is scarce research on the effectiveness of these systems; thus, their viability and applicability are unclear. ObjectiveThe objective of this systematic review is to assess the effectiveness of conversational agents in health care and to identify limitations, adverse events, and areas for future investigation of these agents. MethodsThe 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 the PubMed (Medline), EMBASE, CINAHL, and Web of Science databases will be conducted. Two authors will independently screen the titles and abstracts of the identified references and select studies according to the eligibility criteria. Any discrepancies will then be discussed and resolved. Two reviewers will independently extract and validate data from the included studies into a standardized form and conduct quality appraisal. ResultsAs of January 2020, we have begun a preliminary literature search and piloting of the study selection process. ConclusionsThis systematic review aims to clarify the effectiveness, limitations, and future applications of conversational agents in health care. Our findings may be useful to inform the future development of conversational agents and promote the personalization of patient care. International Registered Report Identifier (IRRID)PRR1-10.2196/16934 Conversational agents (also known as chatbots) have evolved in recent decades to become multimodal, multifunctional platforms with 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 health care. However, there is scarce research on the effectiveness of these systems; thus, their viability and applicability are unclear. The objective of this systematic review is to assess the effectiveness of conversational agents in health care and to identify limitations, adverse events, and areas for future investigation of these agents. 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 the PubMed (Medline), EMBASE, CINAHL, and Web of Science databases will be conducted. Two authors will independently screen the titles and abstracts of the identified references and select studies according to the eligibility criteria. Any discrepancies will then be discussed and resolved. Two reviewers will independently extract and validate data from the included studies into a standardized form and conduct quality appraisal. As of January 2020, we have begun a preliminary literature search and piloting of the study selection process. This systematic review aims to clarify the effectiveness, limitations, and future applications of conversational agents in health care. Our findings may be useful to inform the future development of conversational agents and promote the personalization of patient care. PRR1-10.2196/16934. Conversational agents (also known as chatbots) have evolved in recent decades to become multimodal, multifunctional platforms with 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 health care. However, there is scarce research on the effectiveness of these systems; thus, their viability and applicability are unclear.BACKGROUNDConversational agents (also known as chatbots) have evolved in recent decades to become multimodal, multifunctional platforms with 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 health care. However, there is scarce research on the effectiveness of these systems; thus, their viability and applicability are unclear.The objective of this systematic review is to assess the effectiveness of conversational agents in health care and to identify limitations, adverse events, and areas for future investigation of these agents.OBJECTIVEThe objective of this systematic review is to assess the effectiveness of conversational agents in health care and to identify limitations, adverse events, and areas for future investigation of these agents.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 the PubMed (Medline), EMBASE, CINAHL, and Web of Science databases will be conducted. Two authors will independently screen the titles and abstracts of the identified references and select studies according to the eligibility criteria. Any discrepancies will then be discussed and resolved. Two reviewers will independently extract and validate data from the included studies into a standardized form and conduct quality appraisal.METHODSThe 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 the PubMed (Medline), EMBASE, CINAHL, and Web of Science databases will be conducted. Two authors will independently screen the titles and abstracts of the identified references and select studies according to the eligibility criteria. Any discrepancies will then be discussed and resolved. Two reviewers will independently extract and validate data from the included studies into a standardized form and conduct quality appraisal.As of January 2020, we have begun a preliminary literature search and piloting of the study selection process.RESULTSAs of January 2020, we have begun a preliminary literature search and piloting of the study selection process.This systematic review aims to clarify the effectiveness, limitations, and future applications of conversational agents in health care. Our findings may be useful to inform the future development of conversational agents and promote the personalization of patient care.CONCLUSIONSThis systematic review aims to clarify the effectiveness, limitations, and future applications of conversational agents in health care. Our findings may be useful to inform the future development of conversational agents and promote the personalization of patient care.PRR1-10.2196/16934.INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)PRR1-10.2196/16934. |
| Author | Alturkistani, Abrar Lam, Ching Meinert, Edward Milne-Ives, Madison van Velthoven, Michelle Helena de Cock, Caroline |
| AuthorAffiliation | 1 Digitally Enabled Preventative Health Research Group Department of Paediatrics University of Oxford Oxford United Kingdom 2 Department of Primary Care and Public Health Imperial College London London United Kingdom 3 Institute of Biomedical Engineering Department of Engineering Science University of Oxford Oxford United Kingdom |
| AuthorAffiliation_xml | – name: 2 Department of Primary Care and Public Health Imperial College London London United Kingdom – name: 3 Institute of Biomedical Engineering Department of Engineering Science University of Oxford Oxford United Kingdom – name: 1 Digitally Enabled Preventative Health Research Group Department of Paediatrics University of Oxford Oxford United Kingdom |
| Author_xml | – sequence: 1 givenname: Caroline orcidid: 0000-0001-7585-9598 surname: de Cock fullname: de Cock, Caroline – sequence: 2 givenname: Madison orcidid: 0000-0001-7628-882X surname: Milne-Ives fullname: Milne-Ives, Madison – sequence: 3 givenname: Michelle Helena orcidid: 0000-0003-1245-8759 surname: van Velthoven fullname: van Velthoven, Michelle Helena – sequence: 4 givenname: Abrar orcidid: 0000-0001-7935-8870 surname: Alturkistani fullname: Alturkistani, Abrar – sequence: 5 givenname: Ching orcidid: 0000-0002-9137-749X surname: Lam fullname: Lam, Ching – sequence: 6 givenname: Edward orcidid: 0000-0003-2484-3347 surname: Meinert fullname: Meinert, Edward |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/32149717$$D View this record in MEDLINE/PubMed |
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| Cites_doi | 10.1177/0890117118786866 10.1177/1460458215593329 10.3233/SHTI190661 10.1136/bmj.i4919 10.1055/s-0039-1688757 10.1016/j.ctro.2019.04.002 10.1016/j.eswa.2019.03.054 10.1016/j.pec.2009.02.006 10.1017/s1351324919000329 10.1371/journal.pone.0182151 10.2196/jmir.6553 10.1136/bmj.d5928 10.1177/0706743719828977 10.1080/10810730.2010.499991 10.2196/15360 10.1038/srep42656 10.1111/jgs.12449 10.1093/jamia/ocy072 10.1093/geroni/igy023.1338 10.1109/fads.2017.8253198 10.1136/bmj.g7647 10.1089/rej.2018.2075 10.1145/3267851.3267883 10.1145/357980.357991 10.2196/mental.7785 10.2991/j.jegh.2018.08.104 |
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| Copyright | 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. 2020. This work is licensed under https://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. 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. 2020 |
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| Keywords | virtual assistant chatbot digital health intelligent assistant virtual health care virtual nursing speech recognition software virtual coach avatar artificial intelligence conversational agent voice recognition software |
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| License | 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. |
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| Snippet | Conversational agents (also known as chatbots) have evolved in recent decades to become multimodal, multifunctional platforms with potential to automate a... Background: Conversational agents (also known as chatbots) have evolved in recent decades to become multimodal, multifunctional platforms with potential to... BackgroundConversational agents (also known as chatbots) have evolved in recent decades to become multimodal, multifunctional platforms with potential to... |
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| SubjectTerms | Advanced practice nurses Artificial intelligence Autism Automation Chatbots Chronic illnesses Chronic obstructive pulmonary disease Clinical decision making Clinical trials Decision making Diabetes Feasibility studies Health care Health education Health literacy Health services Keywords Language Mental health Natural language processing Patients Population Protocol Smoking cessation Social skills Software Subject heading schemes Systematic review Telemedicine Voice recognition |
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| Title | Effectiveness of Conversational Agents (Virtual Assistants) in Health Care: Protocol for a Systematic Review |
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