澳大利亚研究发现，用户认可AI医疗摘要质量，但担忧安全与数据使用。
Consumer Attitudes Towards AI in Digital Health: A Mixed-Methods Survey in Australia
- 通过混合方法调研275名澳大利亚消费者，评估对AI医疗的态度。
- AI生成的诊疗摘要在质量与共情上更受青睐，但识别率仅接近随机水平。
- 用户信任依赖具体沟通质量与可见的人类监管，非单纯技术性能。
人工智能在数字健康领域的应用日益广泛。尽管技术性能快速提升，但成功部署的关键在于消费者的接受度，尤其是面向患者的场景。然而，现有研究多停留在抽象层面，缺乏对具体产品形态的评估。本研究在澳大利亚开展混合方法调查（N=275），考察消费者对医疗AI的准备度、接受度、信任感及风险认知，并对比了由AI生成与医生撰写诊疗摘要的场景任务。参与者表现出中等乐观态度，高度认可其有用性与易用性，但也对准确性、安全性及数据使用存在显著担忧。在情景任务中，AI生成摘要在质量、共情和整体实用性上被强烈偏好，但其来源识别率接近随机水平。结果表明，消费者基于具体的沟通质量与可见的人类治理来判断AI，强调需建立临床监督的部署框架，超越单纯的技术性能考量。
原文摘要 · Abstract (English)
AI applications are increasingly being introduced into digital health. While technical performance has advanced rapidly, successful deployment mainly depends on consumer attitudes, especially to patient-facing applications. However, most existing research examines consumer attitudes towards healthcare AI at an abstract level rather than in response to concrete artefacts. We report a mixed-methods survey study in Australia (N=275) examining consumer readiness, acceptance, trust, and risk perceptions of healthcare AI, combined with a scenario-based evaluation of an AI-generated versus clinician-written consultation summary. Participants expressed moderate optimism and strong perceived usefulness and ease of use, but also substantial concerns about accuracy, safety, and data use. In the scenario task, the AI-generated summary was strongly preferred for quality, empathy, and overall usefulness, yet identification of the AI summary was near chance. Findings show that consumers judge AI through concrete communication quality and visible human governance, underscoring the need for clinically supervised deployment frameworks beyond technical performance alone.
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