Design of a Psychological Health Status Evaluation System Under Logistic Model

This paper introduces a mental health status assessment system based on the Logistic regression model. The system mainly consists of a user end, server end, database, web server, and client. Users can assess their mental health status through a browser or mobile terminal, and record and query the assessment results. The server end accesses the database via a web server and displays the assessment results in web page format. To ensure secure storage and transmission of information, the system design also fully considers user privacy protection and data security. The system uses the Logistic regression model as its core algorithm, combining users' personal information and historical data for analysis to predict and evaluate mental health conditions. Experimental results show that the mental health status assessment model based on the Logistic model can achieve an accuracy rate of up to 92.9%. The successful implementation of this system significantly improves the accuracy of mental health assessments. It is of great significance for mental health services in resource-limited environments, playing a crucial role in the development of future mental health assessments.