Characteristics of depression prevalence among college students and analysis of depression influencing factors based on BP neural network modeling

Ran Meng

doi:10.62051/k3s7x306

Authors

Ran Meng

DOI:

https://doi.org/10.62051/k3s7x306

Keywords:

college students, depression prevalence characteristics, BP neural network, depression, influencing factors.

Abstract

Depression is an important influencing factor affecting the mental health of contemporary college students, which has an important impact on the healthy development of college students' physical and mental health and the cultivation of sound personality, and it is of great practical significance to find out the influencing factors affecting college students' depression. This paper adopts a present investigation study, finally selects college students identified as depressed status in 10 universities in S province from January to December 2022 as research subjects, observes their depressive symptoms, analyzes the prevalence characteristics of their depression, and constructs a model of college students' depression influencing factors based on BP neural network to derive the sensitivities of each variable, and evaluates the degree of each factor's influence on college students' depression. The results show that among the 2000 cases of college students who participated in the survey, the number of people who showed depressive state was 134 cases (6.70%), and the incidence of depression among women was slightly higher than that of men in all 134 cases. Gender samples will show significance (p<0.05) for depression status, meaning that different gender samples all show inconsistency and significant differences for depression symptoms. Neural network analysis using spss software showed that the ranking of the importance of the factors affecting the influence of depression among university students was yes: whether there is a family psychiatric disorder > gender > age > whether it is an only child > household registration.

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