Duan XiaoXia
ABSTRACT
With the rapid development of society, an increasing number of individuals are experiencing psychological challenges. Pressures from various aspects of life have contributed to the growing prevalence of conditions such as depression, procrastination, anxiety, obsessive-compulsive disorder, and social phobia. Based on a recent survey, some students at Guangzhou College of Technology and Business exhibit similar issues. However, the current offline psychological consultation model suffers from several limitations, including low evaluation efficiency, limited student engagement, narrow assessment tools, high subjectivity, delayed feedback, insufficient personalized guidance, and inadequate privacy protection. This study aimed to design and develop a mental health assessment and consultation system with intelligent decision support for university students, specifically to enhance the efficiency and effectiveness of mental health management within the institution. The system integrates advanced psychological evaluation instruments and machine learning-based recommendation algorithms, such as Support Vector Machines (SVM), to provide personalized, accurate, and privacy-preserved psychological support. Guided by the User-Centered Design (UCD) model, the system includes basic assessment and consultation functions while also offering intelligent service recommendations to help students access the most suitable psychological resources. Additionally, the system seeks to strengthen its interaction with external social support networks, thereby expanding the psychological assistance channels available to students. The evaluation results indicate that the proposed system meets software quality standards to a “Very Great Extent” based on the ISO 25010 criteria, including functional suitability, performance efficiency, compatibility, usability, reliability, security, maintainability, and portability.
Keywords: Mental Health Assessment and Consulting System, decision support, UCD design model, supporting vector machine (SVM), psychological challenges, ISO 25010 software quality standards
https://doi.org/10.57180/zbne2662