Home
World Journal of Advanced Research and Reviews
International Journal with High Impact Factor for fast publication of Research and Review articles

Main navigation

  • Home
    • Journal Information
    • Editorial Board Members
    • Reviewer Panel
    • Abstracting and Indexing
    • Journal Policies
    • Our CrossMark Policy
    • Publication Ethics
    • Issue in Progress
    • Current Issue
    • Past Issues
    • Instructions for Authors
    • Article processing fee
    • Track Manuscript Status
    • Get Publication Certificate
    • Join Editorial Board
    • Join Reviewer Panel
  • Contact us
  • Downloads

eISSN: 2581-9615 || CODEN: WJARAI || Impact Factor 8.2 ||  CrossRef DOI

Research and review articles are invited for publication in April 2026 (Volume 30, Issue 1) Submit manuscript

Data-driven approaches to mitigate academic stress and improve student mental health

Breadcrumb

  • Home
  • Data-driven approaches to mitigate academic stress and improve student mental health

Awofala Topeola Balkis 1, *, Lateef Adeola Bilikis 2, Edwin Imohimi 3 and Salam Demilade 4

1 Faculty of Health and Life Sciences, De Montfort University, Leicester, United Kingdom.
2 Education Studies, School of Education, University of Hull, Hull, United Kingdom.
3 Department of Information Technology School of Leadership, Information Technology, University of the Potomac, DC, Washington DC, USA.
4 College of Medicine, Faculty of Nursing, Department of Nursing, University of Ibadan, Ibadan, Nigeria.
 
Review Article
World Journal of Advanced Research and Reviews, 2024, 24(03), 2201-2206
Article DOI: 10.30574/wjarr.2024.24.3.3930
DOI url: https://doi.org/10.30574/wjarr.2024.24.3.3930
 
Received on 12 November 2024; revised on 21 December 2024; accepted on 23 December 2024
 
This paper critically examines the efficacy and transformative potential of data-driven methodologies to assess, monitor, and mitigate academic stress, thereby enhancing student mental health. We aim to uncover latent stress patterns and trigger points within academic environments by utilizing a robust framework of advanced analytics, machine learning, and predictive modeling. Applying these technologies allows for the strategic customization of interventions tailored to individual and group needs in real time. By synthesizing data across multiple educational settings—including K-12 schools and higher education institutions—this study provides comprehensive insights into how varied data sources and modeling techniques can be harmonized to effectively detect and address student stress. The outcomes highlighted in this paper demonstrate the significant impact of data-driven methodologies not only in improving student well-being but also in fostering an educational atmosphere that prioritizes mental health. Our findings underscore the critical role that technological integration in educational strategies plays in revolutionizing student support systems and setting a new standard for mental health care within academic institutions.
 
Predictive Analytics; Machine Learning; Academic Stress; Student Mental Health; Educational Interventions
 
https://wjarr.com/sites/default/files/fulltext_pdf/WJARR-2024-3930.pdf

Preview Article PDF

Awofala Topeola Balkis, Lateef Adeola Bilikis, Edwin Imohimi and Salam Demilade. Data-driven approaches to mitigate academic stress and improve student mental health. World Journal of Advanced Research and Reviews, 2024, 24(3), 2201-2206. Article DOI: https://doi.org/10.30574/wjarr.2024.24.3.3930

Copyright © Author(s). All rights reserved. This article is published under the terms of the Creative Commons Attribution 4.0 International License (CC BY 4.0), which permits use, sharing, adaptation, distribution, and reproduction in any medium or format, as long as appropriate credit is given to the original author(s) and source, a link to the license is provided, and any changes made are indicated.


All statements, opinions, and data contained in this publication are solely those of the individual author(s) and contributor(s). The journal, editors, reviewers, and publisher disclaim any responsibility or liability for the content, including accuracy, completeness, or any consequences arising from its use.

Get Certificates

Get Publication Certificate

Download LoA

Check Corssref DOI details

Issue details

Issue Cover Page

Editorial Board

Table of content

Copyright © 2026 World Journal of Advanced Research and Reviews - All rights reserved

Developed & Designed by VS Infosolution