构建医患对话的文化视角
Building a Cultural Perspective on Doctor-Patient Conversations
- IIT Madras（印度理工学院马德拉斯分校）
- Ashoka University（阿肖卡大学）
- Microsoft Research India（微软研究院印度）
机构由 AI 辅助整理，请以论文原文为准。
AI总结：
本研究提出互动文化标记，比较印度与美国真实、模拟及合成医患咨询，发现印度模式为高患者参与强医生控制，合成数据常趋同于美国风格，强调需生成文化基础的合成对话。
AI中文摘要：
AI驱动的医疗抄写员越来越多地被用于转录医患对话并自动化临床文档记录。然而，由于临床对话的敏感性，大规模的真实世界咨询数据集十分稀缺，这导致开发者依赖模拟和LLM生成的合成咨询数据。虽然这些替代方案具有可扩展性，但它们可能无法捕捉临床互动中具有文化情境的模式。我们引入了互动文化标记，即基于跨文化临床沟通的、可测量的医患互动模式，并用它们来比较来自印度和美国临床背景的真实、模拟和合成咨询数据。我们发现参与和控制的不同模式：印度咨询涉及更高的患者参与度但更强的医生控制力，而美国咨询则表现出平衡的参与和开放式讨论。合成的印度咨询往往无法重现这些模式，反而趋向于类似美国的互动。我们识别出额外的合成特征，包括过度的医生解释和公式化的患者回应。最后，我们讨论了生成具有文化基础的合成临床对话的意义。
英文摘要：
AI-powered medical scribes are increasingly used to transcribe doctor-patient conversations and automate clinical documentation. However, large-scale real-world consultation datasets are scarce due to the sensitivity of clinical conversations, leading developers to rely on simulated and LLM-generated synthetic consultations. While scalable, these alternatives may fail to capture culturally situated patterns of clinical interaction. We introduce interactional cultural markers, measurable patterns of doctor-patient interaction grounded in cross-cultural clinical communication, and use them to compare real, simulated, and synthetic consultations from Indian and US clinical contexts. We find distinct patterns of participation and control: Indian consultations involve greater patient participation but stronger doctor control, while US consultations exhibit balanced participation and open-ended discussion. Synthetic Indian consultations often fail to reproduce these patterns, instead converging toward US-like interaction. We identify additional synthetic signatures, including excessive doctor explanation and formulaic patient responses. We conclude by discussing implications for generating culturally grounded synthetic clinical conversations.
