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Public Health Informatics (157) Clinical Informatics (1503) Clinical Information and Decision Making (2157) Depression and Mood Disorders; Suicide Prevention (1802) Methods and New Tools in Mental Health Research (615) Diagnostic Tools in Mental Health (351) Machine Learning (2316) Intentional Self-Harm (148) Digital Biomarkers and Digital Phenotyping (341) Artificial Intelligence (2469) Mental Health Surveillance and Epidemiology (108) Generative Language Models Including ChatGPT (894)

Published on in Vol 11 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/63809, first published .
Human raters and AI models in a meeting, illustrating human vs. AI evaluation.

An Explainable Artificial Intelligence Text Classifier for Suicidality Prediction in Youth Crisis Text Line Users: Development and Validation Study

An Explainable Artificial Intelligence Text Classifier for Suicidality Prediction in Youth Crisis Text Line Users: Development and Validation Study

Authors of this article:

Julia Thomas1, 2, 3 Author Orcid Image ;   Antonia Lucht3 Author Orcid Image ;   Jacob Segler4 Author Orcid Image ;   Richard Wundrack3 Author Orcid Image ;   Marcel Miché1 Author Orcid Image ;   Roselind Lieb1 Author Orcid Image ;   Lars Kuchinke5 Author Orcid Image ;   Gunther Meinlschmidt2, 6, 7, 8 Author Orcid Image
Article Authors Cited by (11) Tweetations Metrics

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  1. Sousa A, Silva E, Brandão M, Rocha F. O USO DA INTELIGÊNCIA ARTIFICIAL NA PREVISÃO DE DEMANDAS EM SAÚDE MENTAL DE POPULAÇÕES VULNERÁVEIS. Revista Contemporânea 2025;5(8):e8879 View
  2. Lumumba V, Muriithi D, Oundo M. Evaluating the Performance of Selected Single Classifiers with Incorporated Explainable Artificial Intelligence (XAI) in the Prediction of Mental Health Distress Among University Students. American Journal of Artificial Intelligence 2025;9(2):133 View
  3. Nagasubramanian H, T. S. S. Reviewing the Effectiveness of Machine Learning Algorithm for Detecting Risk Behaviours Through Speech Patterns. Annals of Neurosciences 2025 View
  4. Boit S, Patil R. A Prompt Engineering Framework for Large Language Model–Based Mental Health Chatbots: Conceptual Framework. JMIR Mental Health 2025;12:e75078 View
  5. Grimland M, Liberman M, Yeshayahu H, Benatov J, Munz N, Segal A, Ben Dayan L, Shenfeld I, Gal K, Levi-Belz Y. Explainable AI for suicide risk detection: gender- and age-specific patterns from real-time crisis chats. Frontiers in Medicine 2025;12 View
  6. Lokadjaja M, Kho J, Schulz P, Goh W. Large Language Models and Their Applications in Mental Health: Scoping Review. JMIR Mental Health 2026;13:e88057 View
  7. Mokheleli T, Makaba T, Ndayizigamiye P, Ndlovu N, Twinomurinzi H. Artificial intelligence in suicide risk assessment: a systematic literature review. Discover Artificial Intelligence 2026;6(1) View
  8. Nazyrova A, Sergaziyev M, Omarbekova A, Sautbayeva L, Akimjan Z, Lamasheva Z. Digital anxiety: psychological effects of social media on women and a human-centered AI framework for mental health support. Frontiers in Computer Science 2026;8 View
  9. Reichenpfader D, Gabarron E, Lüthi S, Bürki J, Kroißenbrunner A, Denecke K. Detecting Suicidal Ideation Signals in Synthetic Conversations with an LLM-Based Mental Health Chatbot: Experimental study. Journal of Technology in Behavioral Science 2026 View

Conference Proceedings

  1. Saduakassova K, Kassenova G, Kamkhen V, Omarkhan A, Tsoy S, Tyumentseva O, Bagin A, Bekmurat O. Proceedings of the 2025 4th International Conference on Public Health and Data Science. USING MACHINE LEARNING METHODS IN PUBLIC HEALTH TO PREVENT SUICIDE AMONG MINORS View
  2. Ma R, Alsoubai A, Park J, Wisniewski P. Proceedings of the 2026 CHI Conference on Human Factors in Computing Systems. From "Fail Fast" to "Mature Safely:" Expert Perspectives as Secondary Stakeholders on Teen-Centered Social Media Risk Detection View