HelpMe: Early Detection of University Students' Mental Health Issues Using a Chatbot-Integrated Dashboard

Nadia Abdul Wahab; Ahmad Asyraf Zainudin; Aznoora Osman; Norfiza Ibrahim; Abdul Hapes Mohammed

doi:10.24191/jcrinn.v10i1.509

HelpMe: Early Detection of University Students' Mental Health Issues Using a Chatbot-Integrated Dashboard

Authors

Nadia Abdul Wahab College of Computing, Informatics and Mathematics, Universiti Teknologi MARA Perlis Branch, Malaysia
Ahmad Asyraf Zainudin College of Computing, Informatics and Mathematics, Universiti Teknologi MARA Perlis Branch, Malaysia
Aznoora Osman College of Computing, Informatics and Mathematics, Universiti Teknologi MARA Perlis Branch, Malaysia
Norfiza Ibrahim College of Computing, Informatics and Mathematics, Universiti Teknologi MARA Perlis Branch, Malaysia
Abdul Hapes Mohammed College of Computing, Informatics and Mathematics, Universiti Teknologi MARA Perlis Branch, Malaysia

DOI:

https://doi.org/10.24191/jcrinn.v10i1.509

Keywords:

mental health screening, chatbot, chatbot-integration, early detection

Abstract

University students face increasing mental health challenges due to academic, social, and financial pressures, yet a shortage of mental health professionals limits early intervention. To bridge this gap, HelpMe—a web-based system with an interactive dashboard and chatbot—was developed for early mental health detection. The system provides a private space for students to monitor their well-being, with the chatbot guiding users through mental health screenings and offering conversational support, while the dashboard visualizes data for tracking emotional states over time. Developed using the Design Science Research Methodology (DSRM), HelpMe follows a structured process of problem identification, system design, and evaluation. The dashboard prioritizes simplicity and engagement, utilizing Power BI for data visualization, while the chatbot ensures a user-friendly mental health screening experience. User Experience Testing (UXT) with 30 university students assessed the system across six key scales, including attractiveness, efficiency, and dependability. Feedback was largely positive, especially regarding simplicity and visual appeal, though challenges were noted in chatbot responsiveness and dashboard efficiency, with occasional delays. This study highlights HelpMe’s potential as an accessible mental health support tool and identifies areas for improvement. Future enhancements will focus on refining chatbot interactions and optimizing real-time dashboard functionality to better support student well-being

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