IDEAS home Printed from https://ideas.repec.org/a/spr/ijsaem/v15y2024i5d10.1007_s13198-023-02052-6.html
   My bibliography  Save this article

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
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s13198-023-02052-6
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s13198-023-02052-6?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Aria, Massimo & Cuccurullo, Corrado, 2017. "bibliometrix: An R-tool for comprehensive science mapping analysis," Journal of Informetrics, Elsevier, vol. 11(4), pages 959-975.
    2. Jun Su Jung & Sung Jin Park & Eun Young Kim & Kyoung-Sae Na & Young Jae Kim & Kwang Gi Kim, 2019. "Prediction models for high risk of suicide in Korean adolescents using machine learning techniques," PLOS ONE, Public Library of Science, vol. 14(6), pages 1-12, June.
    3. van Eck, Nees Jan & Waltman, Ludo, 2008. "Generalizing the h- and g-indices," Journal of Informetrics, Elsevier, vol. 2(4), pages 263-271.
    4. Srinivasan Radhakrishnan & Serkan Erbis & Jacqueline A Isaacs & Sagar Kamarthi, 2017. "Correction: Novel keyword co-occurrence network-based methods to foster systematic reviews of scientific literature," PLOS ONE, Public Library of Science, vol. 12(9), pages 1-1, September.
    5. M. M. Kessler, 1963. "Bibliographic coupling between scientific papers," American Documentation, Wiley Blackwell, vol. 14(1), pages 10-25, January.
    6. Hsin-Ning Su & Pei-Chun Lee, 2010. "Mapping knowledge structure by keyword co-occurrence: a first look at journal papers in Technology Foresight," Scientometrics, Springer;Akadémiai Kiadó, vol. 85(1), pages 65-79, October.
    7. Waltman, Ludo, 2016. "A review of the literature on citation impact indicators," Journal of Informetrics, Elsevier, vol. 10(2), pages 365-391.
    8. Leo Egghe, 2006. "Theory and practise of the g-index," Scientometrics, Springer;Akadémiai Kiadó, vol. 69(1), pages 131-152, October.
    9. Erjia Yan & Ying Ding, 2012. "Scholarly network similarities: How bibliographic coupling networks, citation networks, cocitation networks, topical networks, coauthorship networks, and coword networks relate to each other," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 63(7), pages 1313-1326, July.
    10. Muhammad Farrukh & Fanchen Meng & Yihua Wu & Kalsoom Nawaz, 2020. "Twenty‐eight years of business strategy and the environment research: A bibliometric analysis," Business Strategy and the Environment, Wiley Blackwell, vol. 29(6), pages 2572-2582, September.
    11. Erjia Yan & Ying Ding, 2012. "Scholarly network similarities: How bibliographic coupling networks, citation networks, cocitation networks, topical networks, coauthorship networks, and coword networks relate to each other," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 63(7), pages 1313-1326, July.
    12. Juan Zhang & Qi Yu & Fashan Zheng & Chao Long & Zuxun Lu & Zhiguang Duan, 2016. "Comparing keywords plus of WOS and author keywords: A case study of patient adherence research," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 67(4), pages 967-972, April.
    13. Henry Small, 1973. "Co‐citation in the scientific literature: A new measure of the relationship between two documents," Journal of the American Society for Information Science, Association for Information Science & Technology, vol. 24(4), pages 265-269, July.
    14. Mario Jojoa & Esther Lazaro & Begonya Garcia-Zapirain & Marino J. Gonzalez & Elena Urizar, 2021. "The Impact of COVID 19 on University Staff and Students from Iberoamerica: Online Learning and Teaching Experience," IJERPH, MDPI, vol. 18(11), pages 1-20, May.
    15. van Eck, N.J.P. & Waltman, L., 2008. "Generalizing the h- and g-indices," ERIM Report Series Research in Management ERS-2008-049-LIS, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    16. Howard D. White & Belver C. Griffith, 1981. "Author cocitation: A literature measure of intellectual structure," Journal of the American Society for Information Science, Association for Information Science & Technology, vol. 32(3), pages 163-171, May.
    17. Hsiao, Chun Hua & Yang, Chyan, 2011. "The intellectual development of the technology acceptance model: A co-citation analysis," International Journal of Information Management, Elsevier, vol. 31(2), pages 128-136.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. A. Jiran Meitei & Pratibha Rai & S. S. Rajkishan, 2025. "Application of AI/ML techniques in achieving SDGs: a bibliometric study," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 27(1), pages 281-317, January.
    2. Bo Liu & Wei Song & Qian Sun, 2022. "Status, Trend, and Prospect of Global Farmland Abandonment Research: A Bibliometric Analysis," IJERPH, MDPI, vol. 19(23), pages 1-30, November.
    3. Jun-Ping Qiu & Ke Dong & Hou-Qiang Yu, 2014. "Comparative study on structure and correlation among author co-occurrence networks in bibliometrics," Scientometrics, Springer;Akadémiai Kiadó, vol. 101(2), pages 1345-1360, November.
    4. Julian Andrés Diaz Tautiva & Felipe Ignacio Rifo Rivera & Sebastian Andrés Barros Celume & Sergio Andrés Rifo Rivera, 2024. "Mapping the research about organisations in the latin american context: a bibliometric analysis," Management Review Quarterly, Springer, vol. 74(1), pages 121-169, February.
    5. Yao, Ye & Du, Huibin & Zou, Hongyang & Zhou, Peng & Antunes, Carlos Henggeler & Neumann, Anne & Yeh, Sonia, 2023. "Fifty years of Energy Policy: A bibliometric overview," Energy Policy, Elsevier, vol. 183(C).
    6. Guan-Can Yang & Gang Li & Chun-Ya Li & Yun-Hua Zhao & Jing Zhang & Tong Liu & Dar-Zen Chen & Mu-Hsuan Huang, 2015. "Using the comprehensive patent citation network (CPC) to evaluate patent value," Scientometrics, Springer;Akadémiai Kiadó, vol. 105(3), pages 1319-1346, December.
    7. Yu-Wei Chang & Mu-Hsuan Huang & Chiao-Wen Lin, 2015. "Evolution of research subjects in library and information science based on keyword, bibliographical coupling, and co-citation analyses," Scientometrics, Springer;Akadémiai Kiadó, vol. 105(3), pages 2071-2087, December.
    8. Ying Huang & Wolfgang Glänzel & Lin Zhang, 2021. "Tracing the development of mapping knowledge domains," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(7), pages 6201-6224, July.
    9. Toshiyuki Hasumi & Mei-Shiu Chiu, 2022. "Online mathematics education as bio-eco-techno process: bibliometric analysis using co-authorship and bibliographic coupling," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(8), pages 4631-4654, August.
    10. Perianes-Rodriguez, Antonio & Waltman, Ludo & van Eck, Nees Jan, 2016. "Constructing bibliometric networks: A comparison between full and fractional counting," Journal of Informetrics, Elsevier, vol. 10(4), pages 1178-1195.
    11. Chaoqun Ni & Cassidy R. Sugimoto & Blaise Cronin, 2013. "Visualizing and comparing four facets of scholarly communication: producers, artifacts, concepts, and gatekeepers," Scientometrics, Springer;Akadémiai Kiadó, vol. 94(3), pages 1161-1173, March.
    12. Julián D. Cortés, 2022. "Identifying the dissension in management and business research in Latin America and the Caribbean via co-word analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(12), pages 7111-7125, December.
    13. Davidescu, Adriana AnaMaria & Petcu, Monica Aureliana & Curea, Stefania Cristina & Manta, Eduard Mihai, 2022. "Two faces of the same coin: Exploring the multilateral perspective of informality in relation to Sustainable Development Goals based on bibliometric analysis," Economic Analysis and Policy, Elsevier, vol. 73(C), pages 683-705.
    14. Saurav Chandra Talukder & Zoltán Lakner, 2023. "Exploring the Landscape of Social Entrepreneurship and Crowdfunding: A Bibliometric Analysis," Sustainability, MDPI, vol. 15(12), pages 1-22, June.
    15. Fernando A. F. Ferreira & Sérgio P. Santos, 2021. "Two decades on the MACBETH approach: a bibliometric analysis," Annals of Operations Research, Springer, vol. 296(1), pages 901-925, January.
    16. Hsing Kenneth Cheng & D. Daniel Sokol & Xinyu Zang, 2024. "The rise of empirical online platform research in the new millennium," Journal of Economics & Management Strategy, Wiley Blackwell, vol. 33(2), pages 416-451, March.
    17. Saeed-Ul Hassan & Naif R. Aljohani & Mudassir Shabbir & Umair Ali & Sehrish Iqbal & Raheem Sarwar & Eugenio Martínez-Cámara & Sebastián Ventura & Francisco Herrera, 2020. "Tweet Coupling: a social media methodology for clustering scientific publications," Scientometrics, Springer;Akadémiai Kiadó, vol. 124(2), pages 973-991, August.
    18. Huichen Gao & Shijuan Wang, 2022. "The Intellectual Structure of Research on Rural-to-Urban Migrants: A Bibliometric Analysis," IJERPH, MDPI, vol. 19(15), pages 1-19, August.
    19. Song Yanhui & Wu Lijuan & Qiu Junping, 2021. "A comparative study of first and all-author bibliographic coupling analysis based on Scientometrics," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(2), pages 1125-1147, February.
    20. Siying Li & Huawei Shen & Peng Bao & Xueqi Cheng, 2021. "$$h_u$$ h u -index: a unified index to quantify individuals across disciplines," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(4), pages 3209-3226, April.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:ijsaem:v:15:y:2024:i:5:d:10.1007_s13198-023-02052-6. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.