The Relationship between Depressive Symptoms and Influencing Factors among High School Students: Based on Correlation and Cross-Lagged Panel Network Analysis

Chen Ting; Sun Yan; Li Rui; Wang Yijin

doi:10.16719/j.cnki.1671-6981.20250518

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Journal of Psychological Science ›› 2025, Vol. 48 ›› Issue (5) : 1233-1245. DOI: 10.16719/j.cnki.1671-6981.20250518

Research on Social Psychological Service in the New Era

The Relationship between Depressive Symptoms and Influencing Factors among High School Students: Based on Correlation and Cross-Lagged Panel Network Analysis

Chen Ting, Sun Yan, Li Rui, Wang Yijin

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Abstract

For Chinese adolescents, the high school stage is a critical period for the onset of depression, and this trend has been worsening over the years. Exploring effective methods for prevention and intervention of depression among high school students is of utmost importance. In recent years, an increasing number of researchers have started to utilize network theory of mental disorder to study the internal symptoms of depression. However, there has been inconsistency in the conclusions drawn from network analysis on the core symptoms of adolescent depression in the past. These studies are based on cross-sectional data at a certain point in time and cannot reflect the changes in symptoms over time, leading to different inferences about the importance of symptoms. Therefore, further research on the replicability of the relevant network of depressive symptoms is needed to enhance the reliability of cross-sectional data inference. This study constructed a correlational network of depressive symptoms at two time points, compared the differences in network structure and global strength, and tested whether symptoms with high centrality are consistent across time.
Depression is regarded as a multifaceted and multi-pathway complex process, necessitating a comprehensive examination of its developmental traits based on both the symptoms and influencing factors of depression. This study is guided by an emotional regulation framework and extensive theoretical and empirical evidence. Trait mindfulness, regulatory emotional self-efficacy, emotional empathy, and core self-evaluation were identified from individual factors, while parent-child relationship and friendship quality were identified from situational factors. Cognitive emotion regulation strategies were identified as strategic factors influencing depression among high school students. In addition, compared with male adolescents, female adolescents have significantly higher incidence rates and severity of depression, and their depressive symptoms gradually increase. The severity of depression in female adolescents can persist into adulthood. Cross-lagged panel network analysis can reflect the developmental nature of individual psychological characteristics. This study uses the cross-lagged panel network analysis to explore the dynamic relationship between depressive symptoms and influencing factors in high school students, particularly female high school students.
This study used a cluster random sampling method to select first and second year high school students from two high schools in Dalian and Beipiao cities in Liaoning Province for longitudinal investigation. The two assessments were conducted with a 6-month interval. Ultimately, 1308 participants (585 boys and 723 girls) completed both assessments, aged 15 to 19 years, with an average age of 16.68±0.76 years. Data management, common method bias testing, and descriptive statistical analysis were conducted using SPSS. Correlation network analysis and cross-lagged panel network models were analyzed using R packages, following methodological guidelines developed by the researchers.
The network analysis of depressive symptoms at two time points indicates that sadness, depressed, could not get “going”, and loneliness are central symptoms within the network, representing the core symptoms of depression. There are no significant differences in network structure and global strength between the symptom networks at the two time points, and the importance of core symptoms remains unchanged. Therefore, there is cross-temporal consistency in the inference of core symptoms. The cross-lagged panel network analysis of depressive symptoms among overall high school students and female high school students shows that the core predictive symptoms of depression are both a sense of feelings of failure and unliked. The results of the depression influencing factors cross-lagged panel network analysis showed that self-efficacy in positive emotion regulation, catastrophizing, positive reappraisal, and core self-evaluation were the core influencing factors of depression in high school students. Rational analysis is a core influencing factor of depression unique to female high school students.
In theory, targeting core nodes in a network would most significantly influence the overall network structure, ensuring effective and cost-efficient intervention. In practical applications, we can design intervention strategies focused on the core symptoms and significant predictive factors of depression. It is also possible to intensify interventions targeting core symptoms and important predictive factors within existing intervention plans. Additionally, specialized intervention programs should be developed for female high school students.

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high school students / depression / correlation network analysis / cross-lagged panel network analyses

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Chen Ting, Sun Yan, Li Rui, Wang Yijin. The Relationship between Depressive Symptoms and Influencing Factors among High School Students: Based on Correlation and Cross-Lagged Panel Network Analysis[J]. Journal of Psychological Science. 2025, 48(5): 1233-1245 https://doi.org/10.16719/j.cnki.1671-6981.20250518

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