Abstract
<jats:p>AI-powered conversational agents are becoming part of the everyday Internet information ecosystem, reshaping how users seek, interpret, and act on health-related information outside clinical encounters. As large language model (LLM)-based chatbots are increasingly used as on-demand digital health information tools, understanding how users perceive their credibility, usefulness, and limitations is essential for the responsible design of future Internet-based health services. This mixed-method survey study examined how general adults evaluated healthcare-related question-answer pairs provided by physicians and generated by AI chatbots. Participants (N=62) rated each answer on clarity, usefulness, appropriateness of detail, trustworthiness, and perceived evidence, and provided open-ended explanations of their judgments. Results found that AI-generated responses were rated significantly higher than physician-provided responses overall, t(61) = 8.63, p &amp;lt; 0.001, with significant advantages across all five dimensions. In addition, qualitative findings showed that participants valued detailed, specific, and evidence-like explanations, while expressing concerns about hallucination, privacy, over-reliance, and the need for clinician verification. These findings suggest that LLM-based chatbots may be perceived as useful supplemental information tools within future Internet health ecosystems, but their deployment should include safeguards that support transparency, verification, and appropriate reliance.</jats:p>