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

Chatbots and Conversational Agents (463) Electronic/Mobile Data Capture, Internet-based Survey & Research Methodology (788) Artificial Intelligence (1198) Adoption and Change Management of eHealth Systems (674) E-Health / Health Services Research and New Models of Care (457)

Published on in Vol 24, No 11 (2022): November

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/40681, first published .
Investigating Patients' Continuance Intention Toward Conversational Agents in Outpatient Departments: Cross-sectional Field Survey

Investigating Patients' Continuance Intention Toward Conversational Agents in Outpatient Departments: Cross-sectional Field Survey

Investigating Patients' Continuance Intention Toward Conversational Agents in Outpatient Departments: Cross-sectional Field Survey

Authors of this article:

Xingyi Li1 Author Orcid Image ;   Shirong Xie2 Author Orcid Image ;   Zhengqiang Ye2 Author Orcid Image ;   Shishi Ma3 Author Orcid Image ;   Guangjun Yu4 Author Orcid Image
Article Authors Cited by (4) Tweetations (3) Metrics

Journals

  1. Cai Q, Lin Y, Yu Z. Factors Influencing Learner Attitudes Towards ChatGPT-Assisted Language Learning in Higher Education. International Journal of Human–Computer Interaction 2023:1 View
  2. Tangadulrat P, Sono S, Tangtrakulwanich B. Using ChatGPT for Clinical Practice and Medical Education: Cross-Sectional Survey of Medical Students’ and Physicians’ Perceptions. JMIR Medical Education 2023;9:e50658 View
  3. Min H, Li J, Di M, Huang S, Sun X, Li T, Wu Y. Factors influencing the continuance intention of the women’s health WeChat public account: an integrated model of UTAUT2 and HBM. Frontiers in Public Health 2024;12 View
  4. Liou J, Vo T. Exploring the Relationships among Factors Influencing Healthcare Chatbot Adoption. Sustainability 2024;16(12):5050 View