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. In this paper, we adopt a mixed-methods approach, including surveys (N=167) and interviews (N=17) to investigate how and why the public uses LLMs for healthcare. 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. LLMs provide more accurate information and a more convenient interaction/service model compared to traditional channels. LLMs also do a better job of reducing misinformation, especially in daily healthcare questions. Doctors using LLMs for diagnosis is less acceptable than for auxiliary work such as writing medical records. Based on the findings, we reflect on the ethical and effective use of LLMs for healthcare and propose future research directions.

翻译：大语言模型（LLMs）在生物医学领域已展现出潜力。然而，公众如何将其用于医疗问答、自我诊断及日常保健信息查询等医疗保健目的，目前仍缺乏深入研究。本文采用混合研究方法，包括问卷调查（N=167）和访谈（N=17），旨在探究公众使用大语言模型进行医疗保健的方式及原因。大语言模型作为医疗保健工具已获得普及，并常与搜索引擎、在线健康社区等其他信息渠道结合使用，以优化信息质量。与传统渠道相比，大语言模型能提供更准确的信息和更便捷的交互/服务模式，并在减少错误信息方面表现更优，尤其在日常保健问题中。相较于将大语言模型用于诊断，公众更易接受其用于辅助性工作（如撰写病历）。基于研究结果，我们对大语言模型在医疗保健中的伦理与有效应用进行了反思，并提出了未来研究方向。