People increasingly rely on online sources for health information seeking due to their convenience and timeliness, traditionally using search engines like Google as the primary search agent. Recently, the emergence of generative Artificial Intelligence (AI) has made Large Language Model (LLM) powered conversational agents such as ChatGPT a viable alternative for health information search. However, while trust is crucial for adopting the online health advice, the factors influencing people's trust judgments in health information provided by LLM-powered conversational agents remain unclear. To address this, we conducted a mixed-methods, within-subjects lab study (N=21) to explore how interactions with different agents (ChatGPT vs. Google) across three health search tasks influence participants' trust judgments of the search results as well as the search agents themselves. Our key findings showed that: (a) participants' trust levels in ChatGPT were significantly higher than Google in the context of health information seeking; (b) there is a significant correlation between trust in health-related information and trust in the search agent, however only for Google; (c) the type of search tasks did not affect participants' perceived trust; and (d) participants' prior knowledge, the style of information presentation, and the interactive manner of using search agents were key determinants of trust in the health-related information. Our study taps into differences in trust perceptions when using traditional search engines compared to LLM-powered conversational agents. We highlight the potential role LLMs play in health-related information-seeking contexts, where they excel as stepping stones for further search. We contribute key factors and considerations for ensuring effective and reliable personal health information seeking in the age of generative AI.

翻译：人们日益依赖在线资源获取健康信息，因其便捷性和及时性，传统上以谷歌等搜索引擎作为主要搜索工具。近年来，生成式人工智能的兴起使得基于大型语言模型的对话式代理（如ChatGPT）成为健康信息搜索的可行替代方案。然而，信任对于采纳在线健康建议至关重要，但影响人们对大语言模型驱动型对话代理所提供的健康信息进行信任判断的因素仍不明确。为此，我们采用混合方法的被试内实验室研究（N=21），探究不同代理（ChatGPT与谷歌）在三种健康搜索任务中的交互如何影响参与者对搜索结果及搜索代理本身的信任判断。关键发现表明：（a）在健康信息搜索情境中，参与者对ChatGPT的信任程度显著高于谷歌；（b）对健康相关信息的信任与对搜索代理的信任之间存在显著相关性，但仅针对谷歌；（c）搜索任务类型不影响参与者的感知信任；（d）参与者的先验知识、信息呈现风格及使用搜索代理的交互方式是决定健康相关信息信任的关键因素。本研究揭示了使用传统搜索引擎与大语言模型驱动型对话代理时信任感知的差异。我们强调了大语言模型在健康信息搜索场景中的潜在作用——其作为进一步搜索的基石具有独特优势。同时，我们贡献了确保生成式AI时代个人健康信息搜索有效性与可靠性的关键因素与考量。