测试大模型是否复制东西方抑郁症状差异，发现仅用东方语言提示才部分有效。
Somatic in the East, Psychological in the West?: Investigating Clinically-Grounded Cross-Cultural Depression Symptom Expression in LLMs
- 用东西方人设提示大模型，观察其症状表达差异。
- 英语提示下模型无法复现文化差异，东方语言提示后部分改善。
- 适合关注心理健康AI文化适配性的研究者和开发者。
先前临床心理学研究表明，西方抑郁症患者更常报告心理症状，而东方患者则多表现为躯体症状。本文测试大语言模型（LLMs）在心理健康应用中是否再现这一文化模式，通过向模型输入西方或东方人设进行提示。结果表明，在英文提示下，模型基本无法复现文化差异；而在中文、日文和印地语等主要东方语言提示下，多个配置中表现有所改善。分析揭示失败的两大原因：模型对文化人设敏感度低，且存在强文化不变的症状优先级体系，压制了文化线索。研究显示，尽管提示语言重要，但当前通用大模型仍缺乏稳健的文化感知能力，难以安全有效地用于心理健康场景。
原文摘要 · Abstract (English)
Prior clinical psychology research shows that Western individuals with depression tend to report psychological symptoms, while Eastern individuals report somatic ones. We test whether Large Language Models (LLMs), which are increasingly used in mental health, reproduce these cultural patterns by prompting them with Western or Eastern personas. Results show that LLMs largely fail to replicate the patterns when prompted in English, though prompting in major Eastern languages (i.e., Chinese, Japanese, and Hindi) improves alignment in several configurations. Our analysis pinpoints two key reasons for this failure: the models' low sensitivity to cultural personas and a strong, culturally invariant symptom hierarchy that overrides cultural cues. These findings reveal that while prompt language is important, current general-purpose LLMs lack the robust, culture-aware capabilities essential for safe and effective mental health applications.
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