Somatic in the East, Psychological in the West?: Investigating Clinically-Grounded Cross-Cultural Depression Symptom Expression in LLMs
This work addresses the problem of cultural bias in LLMs for mental health applications, highlighting safety risks, but it is incremental as it builds on prior clinical research and existing LLM evaluation methods.
The study tested whether Large Language Models (LLMs) reproduce known cross-cultural patterns in depression symptom expression, where Western individuals report psychological symptoms and Eastern ones report somatic symptoms, and found that LLMs largely fail to replicate these patterns when prompted in English, though prompting in major Eastern languages improves alignment in some cases.
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.