Loading article...
Loading article...
Stream/Area:
-
Subject:
-
Paper ID:
IJSREM64059
Volume:
10 |
5 |
May 2026
Pages:
1-5
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
Master's of Computer Applications
Bapuji Institute Of f Engineering And Technology
Master's of Computer Applications
Bapuji Institute Of f Engineering And Technology
Mental health issues among students in higher education are increasing due to academic pressure, social challenges, and career uncertainty. This study proposes a Digital Mental Health and Psychological Support System that integrates Machine Learning (ML), Natural Language Processing (NLP), and AI-based chatbot technology to provide self-assessment, mood tracking, and counselor referral services. The system ensures confidentiality, accessibility, and early intervention for psychological conditions. The transition to higher education represents a critical developmental stage for students, often accompanied by a unique set of well-being. The increasing coupled with the limitations of traditional on-campus support services, necessitates the development of innovative and accessible solutions. This project outlines the conceptualization, design, comprehensive specifically tailored to the needs of students in The proposed system is a multifaceted digital platform immediate, confidential, and personalized mental health resources. It aims to between students and mental health support by offering a suite of services, including real-time chat with qualified counselors, an AI-powered conversational agent for preliminary support, a repository of self-help resources, mood tracking and journaling functionalities, and a secure platform for scheduling both virtual and in person appointments. The system is architected to be a proactive and preventative tool, encouraging early intervention and awareness within the university community. By leveraging technology, this project seeks scalable, user friendly, and non-stigmatizing environment where students can freely seek and they need to thrive academically and personally. The development process will follow an agile methodology, ensuring flexibility and responsiveness to user feedback throughout the project lifecycle. The ultimate goal is to deliver a robust and effective only complements existing university extends their reach, making mental healthcare more accessible, approachable, and integrated into the daily lives of students.
KEYWORDS
The Digital Mental Health and Psychological Support System provide an accessible and efficient solution for student well-being. The integration of Machine Learning and AI technologies enables early detection and timely intervention. "The system contributes to improving mental health awareness and support within higher education institutions. The limitations of the traditional, on-campus mental health support model, such as lack of accessibility, stigma, and resource constraints, have created a clear need for a more innovative, scalable, and student-centric solution. This project directly addresses this need by proposing a comprehensive digital platform that leverages technology to provide immediate, confidential, and personalized mental health support. In conclusion, of this Digital Mental Health and Psychological Support System has the potential to make a profound community where every student has the opportunity to thrive. This project is not just about developing a piece of software; it is about investing in the well-being and success of the next generation.
1. Balcombe, L., & De Leo, D. (2021). Digital Mental Health Challenges and the Horizon Ahead for Solutions. JMIR Mental Health, 8(3), e26811. 2. Zhang, M., Scandiffio, J., & Wiljer, D. (2023). The Adoption of AI in Mental Health Care – Perspectives From Professionals. JMIR Formative Research, 7, e47847. 3. Reading Turchioe, M., Desai, P., & Kumar, S. (2024). Perspectives on Artificial Intelligence in Mental Healthcare. Frontiers in Digital Health, 6. 4. Gautam, S., Singh, D., & Chaudhary, A. (2025). AI-Based Self-Assessment Systems for Mental Health. IJERT, 14(05). 5. Alsayed, S., Alkhatib, M., & Shaalan, K. (2024). Impact of AI Chatbots on Student Wellbeing and Mental Health. People and Behavior Analysis, 2(2). 6. Basha, S. E., Gull, M., & Alquqa, E. K. (2025). AI in University Students’ Mental Health: A Review. Discover Social Science & Health, 5, 131. 7. Olla, P., Barnes, A., & Tan, J. (2025). Development of “Luna”, an AI-Based Mental Health Support System in Higher Education. Computers, 14(6), 227.
Publication Date
5/26/2026
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
Documents
Article Views
0
Total views since publication
PDF Downloads
4
Total downloads since publication
Geographic Reach
5
Digital Preservation: This article is permanently archived on Zenodo and complies with all data preservation standards across major indexing platforms.
Plagiarism Screening
This manuscript has been checked for plagiarism using TurnitinPlagiarismChecker software.
Conflict of Interest
The authors declare no conflict of interest related to this research work.
Funding Information
No funding information available for this research.
Related research in the same subject area
Loading similar articles...