{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,3]],"date-time":"2026-08-03T04:46:03Z","timestamp":1785732363378,"version":"3.56.0"},"reference-count":53,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,8,3]],"date-time":"2026-08-03T00:00:00Z","timestamp":1785715200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100004001","name":"Guizhou Provincial Science and Technology Department","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100004001","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Public Health"],"abstract":"<jats:p>Adolescent suicide risk is often expressed through language before it becomes visible in clinical encounters, yet current prevention still relies heavily on episodic screening and limited specialist resources. Large language models (LLMs) may help interpret crisis chats, clinical notes, school-counseling records, and online disclosures, but their relevance to public mental health depends on a practical question: can language signals lead to timely and accountable human action? This mini review examines LLMs in adolescent suicide prevention through this Evidence-to-Action perspective. Current evidence is strongest for supervised risk-signal flagging and more preliminary for context summarization and extraction of suicide-related information from unstructured text. Evidence is much weaker for autonomous generative crisis intervention, especially for adolescents. The main barriers are not only technical accuracy, but also adolescent-specific validation, privacy and consent, cultural variation in distress expression, unsafe generated responses, and unclear responsibility after an algorithmic alert. We argue that near-term deployment should remain under human review and should be judged by whether it improves review timeliness, proportional escalation, safety planning, linkage to care, and equity. LLMs may contribute to adolescent suicide prevention only when embedded in clinically accountable and ethically governed systems. As a focused mini review, this paper maps conceptual boundaries and evidence gaps rather than proposing a validated deployment protocol.<\/jats:p>","DOI":"10.3389\/fpubh.2026.1872450","type":"journal-article","created":{"date-parts":[[2026,8,3]],"date-time":"2026-08-03T04:25:59Z","timestamp":1785731159000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Large language models in adolescent suicide prevention: from language signals to accountable action"],"prefix":"10.3389","volume":"14","author":[{"given":"Man","family":"Li","sequence":"first","affiliation":[{"name":"Department of Psychiatry, Jiaxing Kangci Hospital","place":["Jiaxing, Zhejiang, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wendi","family":"Huang","sequence":"additional","affiliation":[{"name":"Department of Neurology, Third Affiliated Hospital of Zunyi Medical University (The First People's Hospital of Zunyi)","place":["Zunyi, Guizhou, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jingjing","family":"Wu","sequence":"additional","affiliation":[{"name":"Department of Neurology, Third Affiliated Hospital of Zunyi Medical University (The First People's Hospital of Zunyi)","place":["Zunyi, Guizhou, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Nanyu","family":"Kuang","sequence":"additional","affiliation":[{"name":"Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University","place":["Shanghai, China"]},{"name":"Neuroimaging Research Branch, National Institute on Drug Abuse, National Institutes of Health","place":["Baltimore, MD, United States"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yong","family":"Luo","sequence":"additional","affiliation":[{"name":"Department of Neurology, Third Affiliated Hospital of Zunyi Medical University (The First People's Hospital of Zunyi)","place":["Zunyi, Guizhou, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Juan","family":"Huang","sequence":"additional","affiliation":[{"name":"Key Laboratory of Basic Pharmacology and Joint International Research Laboratory of Ethnomedicine of Ministry of Education, Zunyi Medical University","place":["Zunyi, Guizhou, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Nanqu","family":"Huang","sequence":"additional","affiliation":[{"name":"National Drug Clinical Trial Institution, Third Affiliated Hospital of Zunyi Medical University (The First People's Hospital of Zunyi)","place":["Zunyi, Guizhou, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2026,8,3]]},"reference":[{"key":"B1","doi-asserted-by":"publisher","first-page":"e2023064800","DOI":"10.1542\/peds.2023-064800","article-title":"Suicide and suicide risk in adolescents","volume":"153","author":"Hua","year":"2024","journal-title":"Pediatrics"},{"key":"B2","doi-asserted-by":"publisher","first-page":"1217","DOI":"10.1001\/jamapediatrics.2025.3485","article-title":"Suicide interventions for youths: a systematic review","volume":"179","author":"Sim","year":"2025","journal-title":"JAMA Pediatr"},{"key":"B3","doi-asserted-by":"publisher","first-page":"2090","DOI":"10.1177\/15248380231205828","article-title":"Prevalence of suicidal ideation, suicide plans, and suicide attempts among children and adolescents under 18 years of age in Mainland China: a systematic review and meta-analysis","volume":"25","author":"Chang","year":"2024","journal-title":"Trauma Violence Abuse"},{"key":"B4","doi-asserted-by":"publisher","first-page":"57","DOI":"10.3390\/children12010057","article-title":"Suicidal behaviors among United States adolescents: increasing clinical and public health challenges","volume":"12","author":"Ostanin","year":"2025","journal-title":"Children"},{"key":"B5","doi-asserted-by":"publisher","first-page":"1209","DOI":"10.1080\/01612840.2023.2258219","article-title":"Risk factors of suicide attempt among adolescents with suicide ideation in low- and middle-income countries across the globe","volume":"44","author":"Ding","year":"2023","journal-title":"Issues Mental Health Nurs"},{"key":"B6","doi-asserted-by":"publisher","first-page":"187","DOI":"10.1037\/bul0000084","article-title":"Risk factors for suicidal thoughts and behaviors: a meta-analysis of 50 years of research","volume":"143","author":"Franklin","year":"2017","journal-title":"Psychol Bull"},{"key":"B7","doi-asserted-by":"publisher","first-page":"642","DOI":"10.1001\/jamapsychiatry.2019.0174","article-title":"Prediction models for suicide attempts and deaths: a systematic review and simulation","volume":"76","author":"Belsher","year":"2019","journal-title":"JAMA Psychiatry"},{"key":"B8","doi-asserted-by":"publisher","first-page":"951","DOI":"10.1176\/appi.ajp.2018.17101167","article-title":"Predicting suicide attempts and suicide deaths following outpatient visits using electronic health records","volume":"175","author":"Simon","year":"2018","journal-title":"Am J Psychiatry"},{"key":"B9","doi-asserted-by":"publisher","first-page":"39","DOI":"10.1016\/j.jad.2021.06.057","article-title":"Predicting suicide attempts and suicide deaths among adolescents following outpatient visits","volume":"294","author":"Penfold","year":"2021","journal-title":"J Affect Disord"},{"key":"B10","doi-asserted-by":"publisher","first-page":"1261","DOI":"10.1111\/jcpp.12916","article-title":"Predicting suicide attempts in adolescents with longitudinal clinical data and machine learning","volume":"59","author":"Walsh","year":"2018","journal-title":"J Child Psychol Psychiatry Allied Disciplines"},{"key":"B11","doi-asserted-by":"publisher","first-page":"33","DOI":"10.1016\/j.copsyc.2017.07.026","article-title":"Real-time assessment of suicidal thoughts and behaviors","volume":"22","author":"Kleiman","year":"2018","journal-title":"Curr Opin Psychol."},{"key":"B12","doi-asserted-by":"publisher","first-page":"32","DOI":"10.1080\/15374416.2020.1741377","article-title":"Feasibility and acceptability of ecological momentary assessment with high-risk suicidal adolescents following acute psychiatric care","volume":"51","author":"Glenn","year":"2022","journal-title":"J Clin Child Adolesc Psychol"},{"key":"B13","doi-asserted-by":"publisher","first-page":"113","DOI":"10.1007\/s10916-024-02134-3","article-title":"Evaluating of BERT-based and large language mod for suicide detection, prevention, and risk assessment: a systematic review","volume":"48","author":"Levkovich","year":"2024","journal-title":"J Med Syst."},{"key":"B14","doi-asserted-by":"publisher","first-page":"7","DOI":"10.1080\/00332747.2023.2291945","article-title":"Exploring the potential of artificial intelligence in adolescent suicide prevention: current applications, challenges, and future directions","volume":"87","author":"Li","year":"2024","journal-title":"Psychiatry"},{"key":"B15","doi-asserted-by":"publisher","first-page":"e63126","DOI":"10.2196\/63126","article-title":"Applications of large language models in the field of suicide prevention: scoping review","volume":"27","author":"Holmes","year":"2025","journal-title":"J Med Internet Res."},{"key":"B16","doi-asserted-by":"publisher","first-page":"e63809","DOI":"10.2196\/63809","article-title":"An explainable artificial intelligence text classifier for suicidality prediction in youth crisis text line users: development and validation study","volume":"11","author":"Thomas","year":"2025","journal-title":"JMIR Public Health Surveill"},{"key":"B17","doi-asserted-by":"publisher","first-page":"416","DOI":"10.1111\/sltb.13056","article-title":"Predicting suicide risk in real-time crisis hotline chats integrating machine learning with psychological factors: exploring the black box","volume":"54","author":"Grimland","year":"2024","journal-title":"Suicide Life Threaten Behav"},{"key":"B18","doi-asserted-by":"publisher","first-page":"e89873","DOI":"10.7759\/cureus.89873","article-title":"Machine learning models for predicting mental health crises in adolescents using electronic health records: a systematic review","volume":"17","author":"Al-Juhani","year":"2025","journal-title":"Cureus"},{"key":"B19","doi-asserted-by":"publisher","first-page":"114703","DOI":"10.1016\/j.psychres.2022.114703","article-title":"Leveraging unstructured electronic medical record notes to derive population-specific suicide risk models","volume":"315","author":"Levis","year":"2022","journal-title":"Psychiatry Res"},{"key":"B20","doi-asserted-by":"publisher","first-page":"22m14568","DOI":"10.4088\/JCP.22m14568","article-title":"Leveraging natural language processing to improve electronic health record suicide risk prediction for veterans health administration users","volume":"84","author":"Levis","year":"2023","journal-title":"J Clin Psychiatry"},{"key":"B21","doi-asserted-by":"publisher","first-page":"95","DOI":"10.1016\/j.jpsychires.2021.01.052","article-title":"Using weak supervision and deep learning to classify clinical notes for identification of current suicidal ideation","volume":"136","author":"Cusick","year":"2021","journal-title":"J Psychiatric Res"},{"key":"B22","doi-asserted-by":"publisher","first-page":"404","DOI":"10.1038\/s43856-025-01114-z","article-title":"A multi-stage large language model framework for extracting suicide-related social determinants of health","volume":"5","author":"Wang","year":"2025","journal-title":"Commun Med"},{"key":"B23","doi-asserted-by":"publisher","first-page":"46","DOI":"10.1038\/s42256-022-00593-2","article-title":"Human\u2013AI collaboration enables more empathic conversations in text-based peer-to-peer mental health support","volume":"5","author":"Sharma","year":"2023","journal-title":"Nat Machine Intell"},{"key":"B24","doi-asserted-by":"publisher","first-page":"e53562","DOI":"10.2196\/53562","article-title":"Automated behavioral coding to enhance the effectiveness of motivational interviewing in a chat-based suicide prevention helpline: secondary analysis of a clinical trial","volume":"26","author":"Pellemans","year":"2024","journal-title":"J Med Internet Res"},{"key":"B25","doi-asserted-by":"publisher","first-page":"13194","DOI":"10.3390\/ijerph182413194","article-title":"The opportunities and challenges of the first three years of open up, an online text-based counselling service for youth and young adults","volume":"18","author":"Yip","year":"2021","journal-title":"Int J Environ Res Public Health"},{"key":"B26","doi-asserted-by":"publisher","first-page":"e73623","DOI":"10.2196\/73623","article-title":"An examination of generative AI response to suicide inquires: content analysis","volume":"12","author":"Campbell","year":"2025","journal-title":"JMIR Ment Health"},{"key":"B27","doi-asserted-by":"publisher","first-page":"e67891","DOI":"10.2196\/67891","article-title":"Competency of large language models in evaluating appropriate responses to suicidal ideation: comparative study","volume":"27","author":"McBain","year":"2025","journal-title":"J Med Internet Res"},{"key":"B28","doi-asserted-by":"publisher","first-page":"944","DOI":"10.1176\/appi.ps.20250086","article-title":"Evaluation of alignment between large language models and expert clinicians in suicide risk assessment","volume":"76","author":"McBain","year":"2025","journal-title":"Psychiatr Serv"},{"key":"B29","doi-asserted-by":"publisher","first-page":"e47225","DOI":"10.2196\/47225","article-title":"Public Surveillance of social media for suicide using advanced deep learning models in Japan: time series study from 2012 to 2022","volume":"25","author":"Wang","year":"2023","journal-title":"J Med Internet Res"},{"key":"B30","doi-asserted-by":"publisher","first-page":"e57234","DOI":"10.2196\/57234","article-title":"Using large language models to understand suicidality in a social media-based taxonomy of mental health disorders: linguistic analysis of reddit posts","volume":"11","author":"Bauer","year":"2024","journal-title":"JMIR Ment Health"},{"key":"B31","doi-asserted-by":"publisher","first-page":"e34705","DOI":"10.2196\/34705","article-title":"Detecting potentially harmful and protective suicide-related content on twitter: machine learning approach","volume":"24","author":"Metzler","year":"2022","journal-title":"J Med Internet Res"},{"key":"B32","doi-asserted-by":"publisher","first-page":"e76051","DOI":"10.2196\/76051","article-title":"Triaging casual from critical-leveraging machine learning to detect self-harm and suicide risks for youth on social media: algorithm development and validation study","volume":"13","author":"Qadir","year":"2026","journal-title":"JMIR Ment Health"},{"key":"B33","doi-asserted-by":"crossref","DOI":"10.1109\/ICFTIC64248.2024.10913098","article-title":"Utilizing large language models for psychological assessment: enhancing suicide risk detection through social media analysis","volume-title":"2024 6th International Conference on Frontier Technologies of Information and Computer (ICFTIC)","author":"Xu","year":"2024"},{"key":"B34","doi-asserted-by":"publisher","first-page":"e86265","DOI":"10.2196\/86265","article-title":"Suicidal ideation in online spaces through the lens of interpersonal theory of suicide: exploratory study of self-disclosure, peer support, and AI responses","volume":"5","author":"Shimgekar","year":"2026","journal-title":"JMIR AI"},{"key":"B35","doi-asserted-by":"publisher","first-page":"e1002689","DOI":"10.1371\/journal.pmed.1002689","article-title":"Machine learning in medicine: addressing ethical challenges","volume":"15","author":"Vayena","year":"2018","journal-title":"PLoS Med"},{"key":"B36","doi-asserted-by":"publisher","first-page":"119","DOI":"10.1038\/s41746-020-00323-1","article-title":"The future of digital health with federated learning","volume":"3","author":"Rieke","year":"2020","journal-title":"NPJ Digit Med"},{"key":"B37","unstructured":"Ethics and Governance of Artificial Intelligence for Health: Guidance on Large Multi-Modal Models\n          \n          2025"},{"key":"B38","doi-asserted-by":"publisher","first-page":"117160","DOI":"10.1016\/j.psychres.2026.117160","article-title":"Multivariate machine learning regression approaches to predict adolescent suicide risk","volume":"361","author":"Liu","year":"2026","journal-title":"Psychiatry Res"},{"key":"B39","doi-asserted-by":"publisher","first-page":"1544","DOI":"10.1001\/jamainternmed.2018.3763","article-title":"Potential biases in machine learning algorithms using electronic health record data","volume":"178","author":"Gianfrancesco","year":"2018","journal-title":"JAMA Intern Med"},{"key":"B40","doi-asserted-by":"publisher","first-page":"447","DOI":"10.1126\/science.aax2342","article-title":"Dissecting racial bias in an algorithm used to manage the health of populations","volume":"366","author":"Obermeyer","year":"2019","journal-title":"Science"},{"key":"B41","doi-asserted-by":"publisher","first-page":"195","DOI":"10.1038\/s41746-023-00939-z","article-title":"Large language models propagate race-based medicine","volume":"6","author":"Omiye","year":"2023","journal-title":"NPJ Digit Med"},{"key":"B42","doi-asserted-by":"publisher","first-page":"e078378","DOI":"10.1136\/bmj-2023-078378","article-title":"TRIPOD+AI statement: updated guidance for reporting clinical prediction models that use regression or machine learning methods","volume":"385","author":"Collins","year":"2024","journal-title":"BMJ"},{"key":"B43","doi-asserted-by":"publisher","first-page":"e549","DOI":"10.1016\/S2589-7500(20)30219-3","article-title":"Guidelines for clinical trial protocols for interventions involving artificial intelligence: the SPIRIT-AI extension","volume":"2","author":"Rivera","year":"2020","journal-title":"Lancet Digit Health"},{"key":"B44","doi-asserted-by":"publisher","first-page":"924","DOI":"10.1038\/s41591-022-01772-9","article-title":"Reporting guideline for the early-stage clinical evaluation of decision support systems driven by artificial intelligence: DECIDE-AI","volume":"28","author":"Vasey","year":"2022","journal-title":"Nat Med"},{"key":"B45","doi-asserted-by":"publisher","first-page":"m3164","DOI":"10.1136\/bmj.m3164","article-title":"Reporting guidelines for clinical trial reports for interventions involving artificial intelligence: the CONSORT-AI extension","volume":"370","author":"Liu","year":"2020","journal-title":"BMJ"},{"key":"B46","unstructured":"Stade\n              EC\n            \n            \n              Stirman\n              SW\n            \n            \n              Ungar\n              L\n            \n            \n              Boland\n              CL\n            \n            \n              Schwartz\n              HA\n            \n            \n              Yaden\n              DB\n            \n          \n          Toward Responsible Development and Evaluation of LLMs in Psychotherapy\n          \n          2024"},{"key":"B47","doi-asserted-by":"publisher","first-page":"256","DOI":"10.1016\/j.cbpra.2011.01.001","article-title":"Safety planning intervention: a brief intervention to mitigate suicide risk","volume":"19","author":"Stanley","year":"2012","journal-title":"Cogn Behav Pract."},{"key":"B48","doi-asserted-by":"publisher","first-page":"419","DOI":"10.1192\/bjp.2021.50","article-title":"Safety planning-type interventions for suicide prevention: meta-analysis","volume":"219","author":"Nuij","year":"2021","journal-title":"Br J Psychiatry"},{"key":"B49","doi-asserted-by":"publisher","first-page":"675","DOI":"10.1001\/jamapsychiatry.2022.5068","article-title":"Evaluation of the risk identification for suicide and enhanced care model in a native american community","volume":"80","author":"Haroz","year":"2023","journal-title":"JAMA Psychiatry"},{"key":"B50","doi-asserted-by":"publisher","first-page":"362","DOI":"10.1016\/j.csbj.2024.05.004","article-title":"From explainable to interpretable deep learning for natural language processing in healthcare: how far from reality?","volume":"24","author":"Huang","year":"2024","journal-title":"Comput Struct Biotechnol J"},{"key":"B51","doi-asserted-by":"publisher","first-page":"206","DOI":"10.1038\/s42256-019-0048-x","article-title":"Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead","volume":"1","author":"Rudin","year":"2019","journal-title":"Nat Mach Intell."},{"key":"B52","doi-asserted-by":"publisher","first-page":"1778786","DOI":"10.3389\/fdgth.2026.1778786","article-title":"A review for navigating the trade-offs: evaluating open-source and proprietary large language models for clinical and biomedical information extraction","volume":"8","author":"Sugihara","year":"2026","journal-title":"Front Digit Health"},{"key":"B53","doi-asserted-by":"publisher","first-page":"132292","DOI":"10.1016\/j.eswa.2026.132292","article-title":"Geometric prompt optimization: an efficient framework for engineering applications of large language models","volume":"321","author":"Zhang","year":"2026","journal-title":"Expert Syst Appl"}],"container-title":["Frontiers in Public Health"],"original-title":[],"link":[{"URL":"https:\/\/www.frontiersin.org\/articles\/10.3389\/fpubh.2026.1872450\/full","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,8,3]],"date-time":"2026-08-03T04:26:01Z","timestamp":1785731161000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.frontiersin.org\/articles\/10.3389\/fpubh.2026.1872450\/full"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,8,3]]},"references-count":53,"alternative-id":["10.3389\/fpubh.2026.1872450"],"URL":"https:\/\/doi.org\/10.3389\/fpubh.2026.1872450","relation":{},"ISSN":["2296-2565"],"issn-type":[{"value":"2296-2565","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,8,3]]},"article-number":"1872450"}}