Leveraging Mobile Technology for Enhanced Mental Health Levels in University Students

With the advent of the digital era, the application of mobile technology in higher education has become increasingly prevalent, particularly in the management of students’ mental health. University students face multiple pressures, including academic, social, and career-related challenges, which have led to a rise in mental health issues. As a result, the utilization of mobile technology to collect and analyze students’ mental states and behavioral data in realtime has emerged as significant research focus. Current studies predominantly rely on traditional survey methods, which fail to capture students’ dynamic mental states in real-time and often lack an in-depth understanding of complex behavioral patterns. Moreover, few existing studies have examined the integration of multi-source data, thereby limiting comprehensive analyses of mental health risks. This study proposes a dynamic mental behavior inference and mental health risk assessment framework for university students based on multi-source data integration. The framework aims to analyze students’ mental health conditions comprehensively by integrating diverse data from mobile technology. Experimental results and analyses were presented to verify the framework’s effectiveness and practicality, providing new insights for mental health management in higher education and laying the foundation for future research.