mlsanityData to 14 Oct 2026

Patterns vs. Patients: Evaluating LLMs against Mental Health Professionals on Personality Disorder Diagnosis through First-Person Narratives

arXiv 2512.20298 ↗First posted 23 Dec 2025cs.CL cs.AI cs.CYcited by 0

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Abstract (arXiv)

Growing reliance on LLMs for psychiatric self-assessment raises questions about their ability to interpret qualitative patient narratives. This depth over breadth case study directly compares state-of-the-art LLMs and mental health professionals in assessing Borderline (BPD) and Narcissistic (NPD) Personality Disorders based on Polish-language first-person autobiographical accounts. Within our sample, the overall diagnostic scores of the top-performing Gemini Pro models (65.48%) were 21.91 percentage points higher than the average scores of the human professionals (43.57%). While both models and human experts excelled at identifying BPD (F1 = 83.4 & F1 = 80.0, respectively), models severely underdiagnosed NPD (F1 = 6.7 vs. 50.0), showing a potential reluctance toward the value-laden term "narcissism." Qualitatively, models provided confident, elaborate justifications focused on patterns and formal categories, while human experts remained concise and cautious, emphasizing the patients' sense of self and temporal experience. Our findings demonstrate that while LLMs might be competent at interpreting complex first-person clinical data, their outputs still carry critical reliability and bias issues.

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References · 8

  1. 2018UMAP: Uniform Manifold Approximation and Projection for Dimension Reductioncited by 2,898
  2. 2023Towards Understanding Sycophancy in Language Modelscited by 1,040
  3. 2025MMTEB: Massive Multilingual Text Embedding Benchmarkcited by 125
  4. 2020ConvoKit: A Toolkit for the Analysis of Conversationscited by 72
  5. 2024The opportunities and risks of large language models in mental healthcited by 54
  6. 2025Anthropomimetic Uncertainty: What Verbalized Uncertainty in Language Models is Missingcited by 14
  7. 2024Polish-English medical knowledge transfer: A new benchmark and resultscited by 8
  8. 2024A Comprehensive Evaluation of Large Language Models on Mental Illnessescited by 7

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