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Comparing ChatGPT-4o and Gemini 1.5 Pro in Adolescent Psychiatric Emergencies: A Real-World Evaluation of AI Support in Suicide Risk Assessment

  • Ayse Dilara Oztermeli*
  • , Burcu Yıldırım Budak
  • , Vahdet Görmez
  • *Corresponding author for this work
  • Kocaeli City Hospital
  • Istanbul Medeniyet University

Research output: Contribution to journalArticlepeer-review

Abstract

Objective: This study aimed to evaluate the performance of large language models—ChatGPT-4o and Gemini 1.5 Pro—in assessing suicide risk and guiding treatment in adolescents presenting to the emergency department with suicidal ideation and/or attempts. Materials and Methods: A retrospective review was conducted on child psychiatry consultation notes from 36 adolescents evaluated between February and March 2024. Structured clinical data were entered into ChatGPT and Gemini, and the resulting decisions were compared to those made by clinicians regarding hospitalization, sedation need, medication initiation, follow-up timing, and notification of social services or law enforcement. Results: ChatGPT showed higher concordance with clinicians than Gemini, especially in hospitalization (41.6% agreement) and sedation decisions (100% agreement). ChatGPT recommended hospitalization in 58.3% of cases, compared to 33.3% by clinicians and 36.1% by Gemini. For outpatient cases, ChatGPT demonstrated partial alignment with clinical decisions on medication and follow-up, while Gemini’s responses were often uncertain or incomplete. Conclusion: Large language models show promise as decision-support tools in adolescent psychiatric emergencies. ChatGPT was more consistent with clinical judgments than Gemini. However, limitations remain, and further studies involving broader populations are needed before routine clinical integration.

Original languageEnglish
Number of pages12
JournalClinical Child Psychology and Psychiatry
Early online dateApr 2026
DOIs
Publication statusPublished - 24 Apr 2026

Keywords

  • AI in mental health
  • Adolescent psychiatry
  • Artificial intelligence
  • Large language models
  • Psychiatric emergencies
  • Suicide risk assessment

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