Intelligent Conversational Agents in Patient Self-Management: A Systematic Survey Using Multi Data Sources
Open accessAbstract
Intelligent conversation agents (ICAs) have been used for patient self-management and support in recent years. This study systematically reviewed ICA resarch and innovation in academic and industrial institutions using bibliometric and patent analysis. We reported the types of diseases and patients, and the ICAs delivery approaches for patient-self-management. We identified the gaps in the productivity and focused areas.
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Most reviews of conversational agents in health care have limited their focus to a particular health area, agent type, or function.
“Despite the large body of research concerning the application of conversational agents in health care, most reviews have limited their focus to a particular health area, agent type, or function [10,19-22].”
From The Effectiveness of Artificial Intelligence Conversational Agents in Health Care: Systematic Review (2020) · cites this paper as [21]
The majority of reviews on conversational agents in health care focus on a specific therapy area or function.
“Despite a wealth of literature on conversational agents and their application to health care, the majority of reviews on the topic focus on a specific therapy area or function, whereas few reviews have comprehensively examined the overall scope and progress in the field [20-23].”
From Effectiveness of Conversational Agents (Virtual Assistants) in Health Care: Protocol for a Systematic Review (2020) · cites this paper as [22]
Few reviews have comprehensively examined the overall scope and progress in the field of conversational agents in health care.
“Despite a wealth of literature on conversational agents and their application to health care, the majority of reviews on the topic focus on a specific therapy area or function, whereas few reviews have comprehensively examined the overall scope and progress in the field [20-23].”
From Effectiveness of Conversational Agents (Virtual Assistants) in Health Care: Protocol for a Systematic Review (2020) · cites this paper as [22]
Cites
Conversational agents in healthcare: a systematic review
Laranjo, L., Dunn, A. G., Tong, H. L., Kocaballi, A. B., Chen, J., Bashir, R., Surian, D., Gallego, B., Magrabi, F., Lau, A. Y. S., et al. (2018) · Journal of the American Medical Informatics Association · doi:10.1093/jamia/ocy072 · Cited by 1,388 · cited 1× · see citing works
“A recent systematic review on conversational agents in healthcare has shown that ICAs has addressed health issues related to psychotherapy support, education, self-monitoring, and data collection for consumers (e.g., patients), care-giver, or healthcare professionals [3].”
BackgroundProduct review: Covidence (systematic review software)
Babineau, J. (2014) · Journal of the Canadian Health Libraries Association / Journal de l'Association des bibliothèques de la santé du Canada · doi:10.5596/c14-016 · Cited by 721 · cited 1× · see citing works
“The title and abstract fields of the retrieved publications and patent were screened by three of researchers (i.e., ZX, FY, & YQ) via Covidence [5].”
MethodVOS: A New Method for Visualizing Similarities Between Objects
van Eck, N., & Waltman, L. (2006) · Annual Conference of the Gesellschaft für Klassifikation · doi:10.1007/978-3-540-70981-7_34 · Cited by 492 · cited 1× · see citing works
“In this study, VOSviewer [6] was employed to extract and visualize the key terms from both the title and abstract fields for included publication and patent records.”
MethodFabry, B., Ernst, H., Langholz, J., et al. (2006) · doi:10.1016/j.wpi.2005.10.004 · Cited by 135 · cited 1×
“Patents are associated with research and mirror technology development and investment trends in a particular domain [4].”
BackgroundThe Dawn of the Conversational Interface
McTear, M., Callejas, Z., & Griol, D. (2016) · Springer eBooks · doi:10.1007/978-3-319-32967-3_2 · Cited by 20 · cited 1× · see citing works
“The Intelligent conversational agent (ICA) (e.g., Amazon Alexa and Apple Siri) is an application that enables natural language communication with users [1].”
Background
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1 of the 6 references couldn’t be matched to a known paper.
Cited by
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The Effectiveness of Artificial Intelligence Conversational Agents in Health Care: Systematic Review
Milne-Ives, M., de Cock, C., Lim, E., Shehadeh, M. H., de Pennington, N., Mole, G., Normando, E., & Meinert, E. (2020) · Journal of Medical Internet Research · doi:10.2196/20346 · Cited by 626 · see citing works
Anisha, S. A., Sen, A., & Bain, C. (2024) · Journal of Medical Internet Research · doi:10.2196/56114 · Cited by 78 · see citing works
“Some recent previous studies have conducted systematic reviews [27,65,66] or scoping reviews [61,62,67] on CAs in chronic disease management; however, to the best of our knowledge, no review has been conducted yet on the application of AI-based CAs as human-like digital agents for managing NCDs…”
The first AI ‐based Chatbot to promote HIV self‐management: A mixed methods usability study
Ma, Y., Achiche, S., Tu, G., Vicente, S., Lessard, D., Engler, K., Lemire, B., Laymouna, M. A., de Pokomandy, A., Cox, J., et al. (2024) · HIV Medicine · doi:10.1111/hiv.13720 · Cited by 31 · see citing works
“Within health-related IT, chatbots are among the most promising tools, with the potential to revolutionize patient self-management and support [10].”
Ma, Y., Achiche, S., Pomey, M., Paquette, J., Adjtoutah, N., Vicente, S., Engler, K., Laymouna, M. A., Lessard, D., Lemire, B., et al. (2023) · JMIR Research Protocols · doi:10.2196/54668 · Cited by 29 · see citing works
“Often harnessing AI to enable natural language interpretation and assist in decision-making, such tools possess the potential to revolutionize patient self-management and support [13].”
Lin, J., Jaiswal, N., Ma, Y., Lebouché, B., Villanueva, S., Achiche, S., Lessard, D., Engler, K., Berthelot, S., Buckeridge, D. L., et al. (2025) · doi:10.2196/preprints.89852
Lin, J., Jaiswal, N., Ma, Y., Lebouché, B., Villanueva, S., Achiche, S., Lessard, D., Engler, K., Berthelot, S., Buckeridge, D. L., et al. (2026) · JMIR Research Protocols · doi:10.2196/89852
“By providing accessible and reliable health information, chatbots can bridge knowledge gaps, clarify home-management strategies, highlight red flag symptoms, and guide care-seeking options [14].”
Kang, Y., Yan, Y., Wang, T., Yu, Z., Hu, Y., Wang, Z., Zhang, J., Latour, J. M., & Zhang, Y. (2026) · Journal of Medical Internet Research · doi:10.2196/82746 · Cited by 2 · see citing works
de Cock, C., Milne-Ives, M., van Velthoven, M. H., Alturkistani, A., Lam, C., & Meinert, E. (2020) · JMIR Research Protocols · doi:10.2196/16934 · Cited by 62 · see citing works
- Authors
- Zhaopeng, X., Fei, Y., Mustafa, Q. Y. A., Ting, G., Jennifer, W., & Lixin, S.
- Affiliations
- University of North Carolina at Chapel Hill (US)
- Venue
- Studies in Health Technology and Informatics
- Publisher
- IOS Press
- Published
- 2019
- Volume
- 264
- Pages
- 1813-1814
- ISSN
- 0926-9630 (ISSN-L)
- OpenAlex
- W2973004460
- Cited by
- 9
- References
- 6
- Citations by year
- 2026: 2 · 2025: 1 · 2024: 2 · 2023: 2 · 2020: 1 · 2019: 1
- FWCI
- 3.59
- Type
- book chapter
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- cc-by-nc
- Locations
- Studies in health technology and informatics (publishedVersion, cc-by-nc)
- PubMed (publishedVersion)
- PubMed
- Funders
- National Cancer Institute (R21CA212516)
- National Institute of Nursing Research (R01NR016990)
- Topics
- Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Social Sciences › Psychology › Applied Psychology › Digital Mental Health Interventions
- Keywords
- patient self-management, chatbots, bibliometric analysis, patent analysis, research gaps, disease type, patient support
- MeSH terms
- Self-Management, Communication, Humans, Intelligence, Surveys and Questionnaires, Bibliometrics, Information Storage and Retrieval
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