  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.
