Understanding the concerns and choices of public when using large language models for healthcare

• URL: http://arxiv.org/abs/2401.09090v2
• Date: Thu, 12 Sep 2024 16:40:18 GMT
• Title: Understanding the concerns and choices of public when using large language models for healthcare
• Authors: Yunpeng Xiao, Kyrie Zhixuan Zhou, Yueqing Liang, Kai Shu,
• Abstract summary: Large language models (LLMs) have shown their potential in biomedical fields. How the public uses them for healthcare purposes such as medical Q&A, self-diagnosis, and daily healthcare information seeking is under-investigated.
• Score: 17.306501965944978
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Large language models (LLMs) have shown their potential in biomedical fields. However, how the public uses them for healthcare purposes such as medical Q\&A, self-diagnosis, and daily healthcare information seeking is under-investigated. This paper adopts a mixed-methods approach, including surveys (N=214) and interviews (N=17) to investigate how and why the public uses LLMs for healthcare. We found that participants generally believed LLMs as a healthcare tool have gained popularity, and are often used in combination with other information channels such as search engines and online health communities to optimize information quality. Based on the findings, we reflect on the ethical and effective use of LLMs for healthcare and propose future research directions.

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