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

Editorial (51) Infectious Diseases (non-STD/STI) (1770) Chatbots and Conversational Agents (809) Outbreak and Pandemic Preparedness and Management (1856) Theme Issue 2022: Chatbots and COVID-19 (42) Generative Language Models Including ChatGPT (890)

Published on in Vol 26 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/54840, first published .
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Chatbots and COVID-19: Taking Stock of the Lessons Learned

Chatbots and COVID-19: Taking Stock of the Lessons Learned

Authors of this article:

Virginia Arnold1 Author Orcid Image ;   Tina D Purnat2, 3 Author Orcid Image ;   Robert Marten4 Author Orcid Image ;   Andrew Pattison5 Author Orcid Image ;   Hebe Gouda6 Author Orcid Image
Article Authors Cited by (3) Tweetations (3) Metrics

Journals

  1. Haupt M, Yang L, Purnat T, Mackey T. Evaluating the Influence of Role-Playing Prompts on ChatGPT’s Misinformation Detection Accuracy: Quantitative Study. JMIR Infodemiology 2024;4:e60678 View
  2. Girão Carrilho M, Costa Pinto D, Wagner R, Rohden S, Telo de Arriaga M, Quelhas Pinto L. AI-Enabled Digital Health Promotion and Prevention: Computational Literature Review. JMIR AI 2026;5:e84492 View

Conference Proceedings

  1. Lin Z, Li H. Proceedings of the 2025 8th International Conference on Digital Medicine and Image Processing. From Principles to Practice: A Design Framework for Patient-Centered Conversational AI in Digital Medicine View