College Students' Mental Health Support Based on Fuzzy Clustering Algorithm

Area of Science:

• Educational Psychology
• Data Science
• Mental Health Services Research

Background:

• College students in China exhibit low engagement and high data redundancy in ideological and mental health support services.
• Existing discrete optimization models for mental health analysis require predefined data gradient intervals, limiting their flexibility.
• Challenges include low attention, participation, and inefficient data management within current support systems.

Purpose of the Study:

• To investigate and enhance the active participation of college students in ideological and mental health support services.
• To develop a novel evaluation strategy using fuzzy cluster analysis and an improved star discrete analysis model.
• To address limitations of traditional models by offering more dynamic data analysis and tracking capabilities.

Main Methods:

• Application of fuzzy cluster analysis algorithm tailored to different types of student mental health issues.
• Integration with an improved star discrete analysis model for constructing an active participatory evaluation strategy.
• Utilization of the Planck constant factor for classifying ideological and psychological data, enabling hierarchical analysis and quantitative calibration.

Main Results:

• The proposed star discrete analysis model effectively analyzes student participation based on data matching across different levels.
• Demonstrated improvement in the analysis efficiency of data vectors compared to traditional methods.
• The model facilitates matching and tracking of diverse data types for numerical and normal analysis of service participation.

Conclusions:

• The fuzzy cluster analysis combined with the star discrete model offers a reliable and authentic approach to evaluating student participation in mental health services.
• This method overcomes the limitations of traditional models by enabling flexible data matching and tracking.
• The study provides a more effective strategy for understanding and improving college students' engagement with mental health support.