用AI虚拟病人训练医护沟通，提升临终关怀能力
AI Standardized Patient Improves Human Conversations in Advanced Cancer Care
- 构建AI虚拟病人系统，结合大模型与真人对话模拟
- 实验证明使用者在共情、明确表达、赋能患者三方面显著提升
- 适合临床培训、医学教育者及远程医疗学习者
终末期护理中的严重疾病沟通（SIC）面临情绪压力、文化障碍以及希望与诚实之间的平衡难题。尽管其重要性突出，目前临床医生练习SIC的主要方式仍是标准化病人，但该方法成本高、耗时长且缺乏灵活性。本文提出SOPHIE——一个基于大语言模型（LLMs）、拟人化虚拟形象和基于临床文献的个性化自动反馈的AI驱动标准化病人模拟与评估系统，可实现远程、按需的SIC训练。在针对医疗学生与专业人员的随机对照研究中，使用SOPHIE的参与者在三个关键SIC维度（共情、明确表达、赋能）上均表现出显著提升。结果表明，AI工具可有效增强复杂人际沟通技能，为临床医师教育提供可扩展、易获取的解决方案。
原文摘要 · Abstract (English)
Serious illness communication (SIC) in end-of-life care faces challenges such as emotional stress, cultural barriers, and balancing hope with honesty. Despite its importance, one of the few available ways for clinicians to practice SIC is with standardized patients, which is expensive, time-consuming, and inflexible. In this paper, we present SOPHIE, an AI-powered standardized patient simulation and automated feedback system. SOPHIE combines large language models (LLMs), a lifelike virtual avatar, and automated, personalized feedback based on clinical literature to provide remote, on-demand SIC training. In a randomized control study with healthcare students and professionals, SOPHIE users demonstrated significant improvement across three critical SIC domains: Empathize, Be Explicit, and Empower. These results suggest that AI-driven tools can enhance complex interpersonal communication skills, offering scalable, accessible solutions to address a critical gap in clinician education.
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