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Role of AI/ML in the study of mental health problems of the students: a bibliometric study

Author

Listed:
  • S. S. Rajkishan

    (IILM Graduate School of Management)

  • A. Jiran Meitei

    (University of Delhi)

  • Abha Singh

    (Amity University)

Abstract

According to several global burdens of disease reports, mental health issues are a leading cause of disease burden. A worrying trend is the increasing contribution of college students to this pool of mental health woes. Anxiety, depression, stress, and suicidal thoughts are dominant emerging issues. This population cohort's demographic and socio-economic significance has made this an urgent social imperative for everyone. Of late, digital technologies, namely Artificial Intelligence (AI) & Machine Learning (ML)-based models, have gained prominence in resolving mental health issues of young people. This paper employs bibliometric analysis in a nascent attempt to document the research on applying AI & ML-based models in treating mental issues among students. The finding suggests an urgent need to align with the United Nations Sustainable Development Goal 3, "Health and Well-Being", and create awareness at the individual, family, society, university, and country levels and the world at large. China, the USA, and Korea contributed the maximum number of articles. Among the universities, Carnegie Mellon University, the University of Southern California, and Osaka University contributed the most. Evident collaborations between countries and universities are also visible. The top sources include Frontiers in Psychology, the International Journal of Environmental Research & Public Health, and Scientific Reports. The determinations of this study can provide valuable direction toward integrating AI/ML in mental health research.

Suggested Citation

  • S. S. Rajkishan & A. Jiran Meitei & Abha Singh, 2024. "Role of AI/ML in the study of mental health problems of the students: a bibliometric study," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 15(5), pages 1615-1637, May.
  • Handle: RePEc:spr:ijsaem:v:15:y:2024:i:5:d:10.1007_s13198-023-02052-6
    DOI: 10.1007/s13198-023-02052-6
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