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Related Experiment Video

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Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness

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Published on: December 6, 2024

Psychotic episode concurrent with interaction with a large language model (llm): a case report.

Ahmet Selim Başaran¹, Behcet Coşar²

¹Department of Psychiatry, Unye State Hospital, Ordu, Turkey. ahmetselimbasaran@gmail.com.

|June 13, 2026

Summary

Large language models (LLMs) can trigger psychosis relapse by being misinterpreted as personal signals. Early assessment of AI interactions and consistent antipsychotic treatment are crucial for managing patients with schizophrenia.

Keywords:

Aberrant salience Anthropomorphism Ideas of reference Large language models Persecutory delusions Reasoning biases Schizophrenia

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Area of Science:

Psychiatry
Artificial Intelligence
Digital Health

Background:

Large language model (LLM) chat systems generate human-like dialogue that users may anthropomorphize.
Individuals with psychotic-spectrum vulnerability may misinterpret neutral LLM guidance as personalized signals, potentially increasing referential interpretation.

Purpose of the Study:

To present a case where a patient with schizophrenia misinterpreted neutral LLM outputs as personalized signals, leading to medication non-adherence and symptom exacerbation.
To highlight the potential risks of AI chatbot interactions in vulnerable populations and inform clinical practice.

Main Methods:

A case presentation of a 33-year-old male with schizophrenia who began using ChatGPT.
Detailed description of the patient's interaction with the LLM, his subsequent misinterpretations, and the clinical management including medication adjustment.

Main Results:

The patient misinterpreted generic safety tips from ChatGPT as "hidden signs" and personalized warnings.
This led to increased checking behaviors, self-discontinuation of paliperidone, and a significant increase in psychotic symptoms (PANSS score 102, BPRS score 58).

Conclusions:

Neutral LLM statements can be reinterpreted as personally targeted messages in individuals with psychosis, influenced by anthropomorphism, aberrant salience, and reasoning biases.
Routine psychiatric evaluations should include assessments of digital media and AI chatbot use, with explicit discussion of potential misinterpretations and maintenance of antipsychotic treatment to mitigate relapse risk.