Abstract
Background
Identifying important factors contributing to depression is necessary for interrupting risk pathways to minimize adolescent depression. The study aimed to assess the prevalence of depression in high school students and develop a model for identifying risk of depression among adolescents.
Methods
Cross-sectional study was conducted. A total of 1190 adolescents from two high schools in eastern China participated in the study. Artificial neurol network (ANN) was used to establish the identification model.
Results
The prevalence of depression was 29.9% among the students. The model showed the top five protective and risk factors including perceived stress, life events, optimism, self-compassion and resilience. ANN model accuracy was 81.06%, with sensitivity 65.3%, specificity 88.4%, and area under the receiver operating characteristic (ROC) curves 0.846 in testing dataset.
Conclusion
The ANN showed the good performance in identifying risk of depression. Promoting the protective factors and reducing the level of risk factors facilitate preventing and relieving depression.
The prevalence and risk factors of school absenteeism due to premenstrual disorders in Japanese high school students—a school-based cross-sectional study
