Abstract
Background: Adolescence is a high-risk period for depression, especially after the COVID-19 pandemic, when adolescent depression has become increasingly severe. This study employs network analysis to identify core symptoms at various stages. It explores the differences in depression symptom characteristics among Chinese adolescents of different genders during elementary, middle, and high school periods. Methods: A convenience sampling method was used to select 1553 students from various elementary, middle, and high schools in a specific city as participants. Their depression symptoms were assessed using the The Patient Health Questionnaire-9 (PHQ-9) depression screening scale. Using graph theory-based network analysis, this study constructs a depression symptom model via a correlation network and evaluates symptom nodes and their interconnections. Results: The study found significant differences in the detection rates of depression symptoms among the three grade levels (p < 0.001). However, no significant differences were found between male and female students in the detection rates and PHQ-9 scores (p > 0.05). Through network analysis, this study identified the network changes in depression symptoms among Chinese adolescents of different grades and genders. The results show that "depressed mood" is the core symptom in the elementary and high school groups. At the same time, "fatigue" is the central factor affecting the depression network in the middle school group. Negative emotions and fatigue are the primary symptoms that run through the entire adolescent depression network. Conclusions: This study reveals the heterogeneity of depression symptom networks among adolescent groups of different genders and grades, providing a theoretical basis for personalized interventions for adolescent depression in the future.