From predictive algorithms to generative intelligence: a decadal bibliometric mapping of global research frontiers in AI-driven mental health (2016-2025).
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引用次数: 0
Abstract
Objective: The escalating global mental health burden has triggered an urgent real-world need for scalable artificial intelligence (AI) solutions. This study employs a quantitative bibliometric approach to objectively present the research hotspots and emerging trends in the global AI-driven mental health landscape (2016-2025), specifically capturing the post-2023 surge in generative AI.
Methods: We analyzed 9,623 original research articles from Web of Science and Scopus. CiteSpace and VOSviewer were utilized for co-authorship analysis, literature co-citation clustering, and keyword burst detection.
Results: Research output grew exponentially, surpassing 3,000 publications in 2025. The US and China led productivity, with King's College London as the top institution. Research clusters encompass foundational AI methodologies and four clinical domains: diagnosis (e.g., neuroimaging), digital interventions (e.g., chatbots), targeted conditions (e.g., PTSD), and suicide prevention. Recent keyword bursts highlight diagnostic accuracy, loneliness, and occupational burnout as post-2023 frontiers.
Conclusion: The field is transitioning from exploratory algorithmic development to patient-centered clinical applications. While AI offers transformative potential for mental health research and care, future research must urgently prioritize patient safety, algorithmic bias, data privacy, safeguards against algorithmic hallucinations, and ethical integration into clinical workflows to ensure sustainable implementation.
全球精神卫生负担的不断升级引发了对可扩展人工智能（AI）解决方案的迫切需求。本研究采用定量文献计量学方法，客观呈现2016-2025年全球人工智能驱动的心理健康领域的研究热点和新兴趋势，特别是2023年后生成式人工智能的激增。方法：对来自Web of Science和Scopus的9623篇原创研究论文进行分析。利用CiteSpace和VOSviewer进行合著分析、文献共被引聚类和关键词突发检测。成果：科研产出呈指数级增长，2025年超过3000篇。美国和中国在生产率方面领先，伦敦国王学院（King’s College London）位居榜首。研究集群包括基本的人工智能方法和四个临床领域：诊断（例如，神经成像），数字干预（例如，聊天机器人），目标条件（例如，创伤后应激障碍）和自杀预防。最近的关键词爆发强调了诊断准确性、孤独感和职业倦怠是2023年后的前沿。结论：该领域正在从探索性算法开发过渡到以患者为中心的临床应用。虽然人工智能为精神卫生研究和护理提供了变革性潜力，但未来的研究必须紧急优先考虑患者安全、算法偏见、数据隐私、防止算法幻觉的保障措施以及将伦理融入临床工作流程，以确保可持续实施。
期刊介绍：
Australian Journal of Psychology is the premier scientific journal of the Australian Psychological Society. It covers the entire spectrum of psychological research and receives articles on all topics within the broad scope of the discipline. The journal publishes high quality peer-reviewed articles with reviewers and associate editors providing detailed assistance to authors to reach publication. The journal publishes reports of experimental and survey studies, including reports of qualitative investigations, on pure and applied topics in the field of psychology. Articles on clinical psychology or on the professional concerns of applied psychology should be submitted to our sister journals, Australian Psychologist or Clinical Psychologist. The journal publishes occasional reviews of specific topics, theoretical pieces and commentaries on methodological issues. There are also solicited book reviews and comments Annual special issues devoted to a single topic, and guest edited by a specialist editor, are published. The journal regards itself as international in vision and will accept submissions from psychologists in all countries.
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