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Related Experiment Video

Updated: Sep 10, 2025

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness
03:14

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Development and evaluation of LLM-based suicide intervention chatbot.

Xueting Cui1,2, Yun Gu1,2, Hui Fang3

  • 1State Key Laboratory of Cognitive Science and Mental Health, Institute of Psychology, Chinese Academy of Sciences (CAS), Beijing, China.

Frontiers in Psychiatry
|August 21, 2025
PubMed
Summary

A new suicide intervention chatbot, powered by Large Language Models (LLMs), offers effective, large-scale, and rapid self-help for individuals experiencing suicidal ideation. This AI-driven tool provides crucial emotional support and therapeutic intervention, addressing limitations of traditional methods.

Keywords:
chatbotlarge language modelself-help psychological crisis interventionsuicidal ideationsuicide prevention and intervention

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Area of Science:

  • Digital Health
  • Artificial Intelligence in Mental Health
  • Suicidology

Background:

  • Suicide causes over 720,000 global deaths annually, necessitating scalable interventions.
  • Traditional suicide interventions face challenges like practitioner shortages and high costs.

Purpose of the Study:

  • To develop and evaluate an effective suicide intervention chatbot using Large Language Models (LLMs).
  • To provide early, large-scale, and rapid self-help interventions for individuals with suicidal ideation.

Main Methods:

  • Fine-tuned ChatGPT-4 using prompt engineering based on psychological crisis intervention methods.
  • Developed a self-help web-based dialogue platform powered by the LLM-based chatbot.
  • Evaluated the chatbot's usability and intervention efficacy.

Main Results:

  • The chatbot demonstrated high effectiveness and quality across user interface, interaction, emotional support, and intervention efficacy.
  • Users reported high satisfaction with the chatbot's safety, privacy, and overall experience.
  • The intervention showed significant promise in providing accessible mental health support.

Conclusions:

  • LLM-powered chatbots can deliver effective emotional support and therapeutic interventions for individuals experiencing suicidal ideation.
  • This technology offers a scalable solution to supplement traditional mental health services.
  • The developed chatbot shows potential for widespread adoption in suicide prevention efforts.