Influencing Factors of Mental Health Issues among Adolescents

Abstract

This paper focuses on exploring the influencing factors of mental health issues. Utilizing a binary Logit regression model and a dataset comprising 1,000 samples, it examines the impact of four key variables-stress level, sleep duration, working hours, and physical activity duration-on mental health status. The analytical results reveal that the p-values of all four variables exceed 0.05, indicating that none of them exert a statistically significant effect on mental health. Additionally, the overall prediction accuracy of the model stands at 54.30%, reflecting poor predictive performance. The study suggests that the underperformance of the model may be attributed to weak correlations between the selected variables, the omission of complex factors such as family environment, and limitations in measurement methods. To enhance the explanatory power and prediction accuracy for population mental health issues and provide a solid foundation for formulating intervention strategies, future research should expand the range of variables, optimize measurement methods, and experiment with alternative models.