Students' Mental Health Data and Construction of Feedback System Based on Ordered Variable Regression Model

Abstract

with the continuous rise of people's living standards, more and more researchers begin to pay attention to the mental health problems of teenagers. We not only need to care about students' all-round development, but also pay attention to students' mental health development. At present, the detection and analysis of students' mental health data in most colleges and universities are in the basic stage, and there are many difficulties in data analysis and result feedback. Based on the above situation, this paper proposes to use the ordered variable regression model to analyze and construct the students' mental health data. Ordinal variable regression model can reasonably explain and predict psychological phenomena. Firstly, the parameter inspection method is used to judge the influencing factors, and then the screening function is used to classify and check the overall data. Finally, the data fusion algorithm is used to optimize the feedback function of students' mental health evaluation. The results show that the optimized regression model can solve the error of data feedback and improve the effect of data evaluation. It can accurately judge students' mental health status and provide effective services for colleges and universities to deal with students' mental health problems. Under the condition of large amount of data, the ordered variable regression model can also accurately deal with the prediction task and explain the factors affecting the changes of students' mental health.