The Development of a Depression Risk Assessment System Using Data Mining

This research aimed to develop a depression risk assessment system using data mining principles. The system was developed as a web application accessible via both computers and mobile devices, utilizing the Thai version of the Center for Epidemiologic Studies Depression Scale (CES-D) as the primary screening tool, combined with data mining techniques to analyze patterns and relationships of factors contributing to depression. The system features a user-friendly interface, comprising a 20-item questionnaire assessment section and a dashboard displaying easy-to-understand analytical results. The system was tested with a sample of 400 students from the Faculty of Management Science at Phetchaburi Rajabhat University. The research findings revealed that 27.50% of students were at risk of developing depression. Analysis using Association Rule data mining techniques identified several significant factors correlated with depression. The highest risk was found among third-year students at 45%, followed by students living in off-campus accommodation (33.33%), students from divorced families (31.82%), and female students (31.58%). Additionally, analysis by academic major showed that students in Business Information Management had the highest rate of depression.