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Background <p>Suicide and depression among children and adolescents represent critical global public health challenges. Despite a rapidly growing body of literature, the overall knowledge structure, research trends, and emerging directions in this field remain insufficiently synthesized.</p> Objective <p>This study aimed to perform a comprehensive bibliometric analysis of research on suicide and depression among children and adolescents, with a focus on thematic evolution, global research trends, and emerging areas to guide future research directions.</p> Methods <p>A bibliometric analysis was conducted using the Web of Science Core Collection (WoSCC) database to identify relevant publications from 2005 to April 6, 2026. Original articles and review papers were included. Data were analyzed using Bibliometrix (R package), VOSviewer, and InCites to evaluate publication trends, contributing countries, institutions, journals, collaboration networks, and keyword co-occurrence patterns.</p> Results <p>A total of 8454 publications were included, demonstrating a steady increase in annual output, particularly after 2018, with a strong concentration in high-impact (Q1) journals. The United States and China were the leading contributors in terms of productivity, citations, and international collaboration. Core research themes included depression, suicide, and adolescent mental health, while five major thematic clusters were identified: clinical comorbidity, self-harm behaviors, social determinants and prevention, psychological mechanisms, and artificial intelligence-driven applications. Over time, research focus has shifted from traditional clinical and epidemiological approaches to integrative, data-driven frameworks. Emerging hotspots include machine learning, prediction models, ecological momentary assessment, and digital phenotyping.</p> Conclusions <p>Research on suicide and depression in children and adolescents has expanded substantially and is evolving toward interdisciplinary and precision-oriented paradigms. Advances in artificial intelligence and data analytics are reshaping early detection and prevention strategies. However, disparities in global research contributions and challenges in translating technological innovations into clinical practice persist. Future efforts should emphasize equitable collaboration, longitudinal data integration, and real-world implementation to enhance mental health outcomes in youth.</p>

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A bibliometric analysis of global research trends and emerging hotspots on suicide and depression among children and adolescents

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年7月9日

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  • Ziming Liu,
  • Shumin Zhu,
  • Yulan Geng

摘要

Background

Suicide and depression among children and adolescents represent critical global public health challenges. Despite a rapidly growing body of literature, the overall knowledge structure, research trends, and emerging directions in this field remain insufficiently synthesized.

Objective

This study aimed to perform a comprehensive bibliometric analysis of research on suicide and depression among children and adolescents, with a focus on thematic evolution, global research trends, and emerging areas to guide future research directions.

Methods

A bibliometric analysis was conducted using the Web of Science Core Collection (WoSCC) database to identify relevant publications from 2005 to April 6, 2026. Original articles and review papers were included. Data were analyzed using Bibliometrix (R package), VOSviewer, and InCites to evaluate publication trends, contributing countries, institutions, journals, collaboration networks, and keyword co-occurrence patterns.

Results

A total of 8454 publications were included, demonstrating a steady increase in annual output, particularly after 2018, with a strong concentration in high-impact (Q1) journals. The United States and China were the leading contributors in terms of productivity, citations, and international collaboration. Core research themes included depression, suicide, and adolescent mental health, while five major thematic clusters were identified: clinical comorbidity, self-harm behaviors, social determinants and prevention, psychological mechanisms, and artificial intelligence-driven applications. Over time, research focus has shifted from traditional clinical and epidemiological approaches to integrative, data-driven frameworks. Emerging hotspots include machine learning, prediction models, ecological momentary assessment, and digital phenotyping.

Conclusions

Research on suicide and depression in children and adolescents has expanded substantially and is evolving toward interdisciplinary and precision-oriented paradigms. Advances in artificial intelligence and data analytics are reshaping early detection and prevention strategies. However, disparities in global research contributions and challenges in translating technological innovations into clinical practice persist. Future efforts should emphasize equitable collaboration, longitudinal data integration, and real-world implementation to enhance mental health outcomes in youth.