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

Chatbots and Conversational Agents (1172) Patient Education for Cancer (327) Artificial Intelligence (4750) Knowledge and Attitudes of Mental Health Professionals towards Digital Interventions (84) AI Language Models in Health Care (741) Ethical, Legal, and Social Issues in AI (209)

Published on in Vol 27 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/71418, first published .
Young cancer patient in hospital gown and beanie receiving IV treatment

Perceptions and Attitudes of Chinese Oncologists Toward Endorsing AI-Driven Chatbots for Health Information Seeking Among Patients with Cancer: Phenomenological Qualitative Study

Perceptions and Attitudes of Chinese Oncologists Toward Endorsing AI-Driven Chatbots for Health Information Seeking Among Patients with Cancer: Phenomenological Qualitative Study

Authors of this article:

Lijuan Zeng1 Author Orcid Image ;   Qiaoqi Li1 Author Orcid Image ;   Yan Zuo2, 3, 4 Author Orcid Image ;   Ying Zhang5 Author Orcid Image ;   Zhaojun Li6 Author Orcid Image
Article Authors Cited by (5) Tweetations Metrics

Journals

  1. Alon L, Levkovich I. Consumer and Patient Health Information Seeking with Generative AI Tools: A Scoping Review of Facilitators and Barriers (Preprint). Journal of Medical Internet Research 2026 View
  2. Huang Y, Liang Q, Lin Z, Zhang M, Liu X, Ding L, Peng R, Yu R. AI chatbots for health information seeking among Chinese patients with precancerous ENT lesions: a descriptive qualitative study. BMJ Open 2026;16(5):e102637 View
  3. Wang X, Li L, Cai X, Luo W, Shen M, Zuo Y, Zhang J, Bai Z, Yao Y, Zhang M, Zhang Y. Preparedness for generative AI adoption among Chinese cancer survivors: a multi-center cross-sectional survey study. Frontiers in Public Health 2026;14 View
  4. Zhang L, Huai P, Xu R, Sun J, Jin R, Lv H. Application of Large Language Models in Chronic Disease Care: Mixed Methods Systematic Review and Thematic Synthesis. Journal of Medical Internet Research 2026;28:e90744 View
  5. Wang Z, Hu J, Zheng X. Stakeholder Perspectives on AI-Assisted Pain Assessment in Pediatrics: A Qualitative Study of Shared Needs and Divergent Priorities. The Journal of Pain 2026:106415 View