This paper is in the following e-collection/theme issue:

Digital Health Reviews (1309) Chatbots and Conversational Agents (539) Artificial Intelligence (1400) Text-messaging (SMS, WeChat etc)-Based Interventions (655)

Published on in Vol 25 (2023)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/46548, first published .
Factors Influencing the Acceptability, Acceptance, and Adoption of Conversational Agents in Health Care: Integrative Review

Factors Influencing the Acceptability, Acceptance, and Adoption of Conversational Agents in Health Care: Integrative Review

Factors Influencing the Acceptability, Acceptance, and Adoption of Conversational Agents in Health Care: Integrative Review

Authors of this article:

Maximilian Wutz1 Author Orcid Image ;   Marius Hermes1 Author Orcid Image ;   Vera Winter1 Author Orcid Image ;   Juliane Köberlein-Neu1 Author Orcid Image
Article Authors Cited by (13) Tweetations (7) Metrics

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  1. Alanzi T, Almahdi R, Alghanim D, Almusmili L, Saleh A, Alanazi S, Alshobaki K, Attar R, Al Qunais A, Alzahrani H, Alshehri R, Sulail A, Alblwi A, Alanzi N, Alanzi N. Factors Affecting the Adoption of Artificial Intelligence-Enabled Virtual Assistants for Leukemia Self-Management. Cureus 2023 View
  2. Weber S, Wyszynski M, Godefroid M, Plattfaut R, Niehaves B. How do medical professionals make sense (or not) of AI? A social-media-based computational grounded theory study and an online survey. Computational and Structural Biotechnology Journal 2024;24:146 View
  3. Laymouna M, Ma Y, Lessard D, Schuster T, Engler K, Lebouché B. Roles, Users, Benefits, and Limitations of Chatbots in Health Care: Rapid Review. Journal of Medical Internet Research 2024;26:e56930 View
  4. Ellis J, Hamer M, Akerson M, Andazola M, Moore A, Campbell E, DeCamp M. Patient Perceptions of Chatbot Supervision in Health Care Settings. JAMA Network Open 2024;7(4):e248833 View
  5. Ng W, Lau N, Lee V, Vijayakumar S, Leong Q, Ooi S, Su L, Lee Y, Chan S, Blasiak A, Ho D. Shaping Adoption and Sustained Use Across the Maternal Journey: Qualitative Study on Perceived Usability and Credibility in Digital Health Tools. JMIR Human Factors 2024;11:e59269 View
  6. Zagulova D, Kolobovnikova J, Pozdnyakova N, Mansharipova A. Acceptance of Mhealth by Patients with Cardiovascular Diseases: the Structural Model of Health Applications Use. The Russian Archives of Internal Medicine 2024;14(4):260 View
  7. Pellemans M, Salmi S, Mérelle S, Janssen W, van der Mei R. Automated Behavioral Coding to Enhance the Effectiveness of Motivational Interviewing in a Chat-Based Suicide Prevention Helpline: Secondary Analysis of a Clinical Trial. Journal of Medical Internet Research 2024;26:e53562 View
  8. Kaphingst K, Kohlmann W, Lorenz Chambers R, Bather J, Goodman M, Bradshaw R, Chavez-Yenter D, Colonna S, Espinel W, Everett J, Flynn M, Gammon A, Harris A, Hess R, Kaiser-Jackson L, Lee S, Monahan R, Schiffman J, Volkmar M, Wetter D, Zhong L, Mann D, Ginsburg O, Sigireddi M, Kawamoto K, Del Fiol G, Buys S. Uptake of Cancer Genetic Services for Chatbot vs Standard-of-Care Delivery Models. JAMA Network Open 2024;7(9):e2432143 View
  9. Franc J, Hertelendy A, Cheng L, Hata R, Verde M. Accuracy of a Commercial Large Language Model (ChatGPT) to Perform Disaster Triage of Simulated Patients Using the Simple Triage and Rapid Treatment (START) Protocol: Gage Repeatability and Reproducibility Study. Journal of Medical Internet Research 2024;26:e55648 View
  10. Peng C, Zhang S, Wen F, Liu K. How loneliness leads to the conversational AI usage intention: the roles of anthropomorphic interface, para-social interaction. Current Psychology 2024 View
  11. Stamate A, Marzan M, Velciu M, Paul C, Spiru L. Advancing user-centric design and technology adoption for aging populations: a multifaceted approach. Frontiers in Public Health 2024;12 View

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  1. Yang M, Guo Y. Human-Computer Interaction. View
  2. Chen Z, Zhao X, Hua M, Xu J. HCI International 2024 – Late Breaking Papers. View