Research on the Construction of Psychological Profiles of College Students and the Practice of Precise Psychological Education Supported by Cluster Analysis Technology

Currently, mental health issues among college students have become a complex and pressing reality, necessitating a systematic and scientific intervention strategy for addressing mental health crises among this population.This study first explored a method for obtaining optimal solutions by utilizing an improved artificial bee colony algorithm to derive initial cluster centers, followed by the application of the ABC-SC algorithm in the optimization process of fuzzy clustering algorithms.Subsequently, based on the characteristics of mental health data among college students, a user profile suitable for mental health questionnaire data was established.Finally, a 12-week experimental intervention was conducted on college students from a certain university to experimentally test the effectiveness of the proposed method in improving college students' mental health status.By using the Symptom Checklist-90 (SCL-90) to assess college students' mental health, it was found that the proposed method significantly improved symptoms of depression, anxiety, hostility, phobia, somatization, obsessive-compulsive disorder, paranoia, and interpersonal relationships.