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

Pilot studies (non-ehealth) (80) Artificial Intelligence (1740) AI Language Models in Health Care (106) Generative Language Models Including ChatGPT (497) Vaccination and Immunization in the Digital Age (401) Language Translation Technologies for Medicine and Public Health (19) Information Quality in Digital Media (374) Information Retrieval (323)

Published on in Vol 8 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/60939, first published .
Ensuring Accuracy and Equity in Vaccination Information From ChatGPT and CDC: Mixed-Methods Cross-Language Evaluation

Ensuring Accuracy and Equity in Vaccination Information From ChatGPT and CDC: Mixed-Methods Cross-Language Evaluation

Ensuring Accuracy and Equity in Vaccination Information From ChatGPT and CDC: Mixed-Methods Cross-Language Evaluation

Authors of this article:

Saubhagya Joshi1 Author Orcid Image ;   Eunbin Ha1 Author Orcid Image ;   Andee Amaya1 Author Orcid Image ;   Melissa Mendoza1 Author Orcid Image ;   Yonaira Rivera1 Author Orcid Image ;   Vivek K Singh1 Author Orcid Image
Article Authors Cited by (2) Tweetations Metrics

Journals

  1. Bragazzi N, Buchinger M, Atwan H, Tuma R, Chirico F, Szarpak L, Farah R, Khamisy-Farah R. Proficiency, Clarity, and Objectivity of Large Language Models Versus Specialists’ Knowledge on COVID-19's Impacts in Pregnancy: Cross-Sectional Pilot Study. JMIR Formative Research 2025;9:e56126 View
  2. Hack S, Alsleibi S, Saleh N, Alon E, Rabinovics N, Remer E. Are chatbots a reliable source for patient frequently asked questions on neck masses?. European Archives of Oto-Rhino-Laryngology 2025 View