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在狼疼痛中集中患者的声音:使用大型语言模型对Reddit叙述的生物心理社会分析

Andrew Walker¹, Jerik Leung², Aishwarya Alagappan³

¹Deparment of Biomedical Informatics, Emory University School of Medicine, Atlanta, Georgia.

Arthritis care & research

|October 28, 2025

概括

大型语言模型 (LLM) 分析了Reddit数据,以了解狼疼痛经历. 这揭示了临床环境中常常错过的关键的心理社会和脑膜疼痛维度.

科学领域:

类风湿病学类风湿病学
自然语言处理自然语言处理.
数字健康数字健康

背景情况:

在线患者社区提供丰富的慢性疾病经验数据.
了解狼疼痛的多维性质对于有效管理至关重要.
传统的临床环境可能低估了疼痛的心理社会和文化方面.

研究的目的:

将自然语言处理 (NLP) 和大型语言模型 (LLM) 应用于Reddit讨论中.
在生物心理社会框架内对狼患者的多维疼痛体验进行表征.
确定与疼痛投诉,管理和患者报告的结果相关的主题.

主要方法:

从狼特定的子reddits (2010年6月-2023年12月) 中提取的Reddit帖子.
使用临床词汇和应用主题建模来识别与疼痛相关的帖子.
利用了对生物心理社会模型进行微调的LLM,用于总结生成和内容分析.

主要成果:

分析了来自10,857名作者的31,785条帖子,确定了疼痛的维度 (社会文化,情感,非塑性).
由LLM生成的摘要显示了适度的主题准确性 (3.1/4) 和内容覆盖率 (2.9/4).
诺西普拉斯疼痛是普遍存在的 (56.3%),以及重要的社会文化方面,如同行支持 (33.8%) 和提供者问题 (10.1%).

结论:

从网络狼社区中,NLP和LLM可以提取有价值的多维疼痛见解.
这些方法突出了代表性不足的心理,社会和文化疼痛方面.
通过整合在线社区数据,研究结果支持通过整合在线社区数据,在风湿病学中加强以患者为中心的护理.

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