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Accepted for/Published in: JMIR AI

Date Submitted: Jul 7, 2025
Date Accepted: Jan 19, 2026

The final, peer-reviewed published version of this preprint can be found here:

Human–Generative AI Interactions and Their Effects on Beliefs About Health Issues: Content Analysis and Experiment

Lu L, Wang YS, Liu J, McLeod DM

Human–Generative AI Interactions and Their Effects on Beliefs About Health Issues: Content Analysis and Experiment

JMIR AI 2026;5:e80270

DOI: 10.2196/80270

PMID: 41637732

PMCID: 12917482

Human-Generative AI Interactions and Their Effects on Beliefs About Health Issues: A Content Analysis and Experiment

  • Linqi Lu; 
  • Yanshu Sybil Wang; 
  • Jiawei Liu; 
  • Douglas M. McLeod

ABSTRACT

This study examined how interactions with ChatGPT to evaluate information about flu vaccination and climate change influenced users’ beliefs and attitudes. Results from an online experiment using a pretest-posttest design with 149 university students showed that ChatGPT consistently utilized coherence appeals (providing explanations against inaccurate information) while the use of other strategies, such as consensus appeals (highlighting the agreement among experts), credibility appeals (showcasing official agencies’ statements), verification appeals (encouraging users to cross-check information), and empathy appeals (acknowledging users’ concerns) varied by topic. For flu vaccination, interactions with ChatGPT were associated with reduced misconceptions and increased support for flu vaccination. For climate change, interactions with ChatGPT were not associated with changes in misconceptions (possibly because baseline misconceptions regarding climate change were relatively low) but increased support for climate action.


 Citation

Please cite as:

Lu L, Wang YS, Liu J, McLeod DM

Human–Generative AI Interactions and Their Effects on Beliefs About Health Issues: Content Analysis and Experiment

JMIR AI 2026;5:e80270

DOI: 10.2196/80270

PMID: 41637732

PMCID: 12917482

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