Network structure analysis of post-traumatic stress and depressive symptoms among college students: identification of...

The comorbidity between post-traumatic stress disorder (PTSD) and depression has received increasing attention among college students; however, the interaction mechanisms at the symptom level remain unclear. This study employed network analysis to construct a cross-diagnostic network structure of post-traumatic stress and depressive symptoms among college students, identifying central symptoms and bridge symptoms to provide empirical evidence for precision-oriented psychological interventions.

A cross-sectional survey was conducted among 501 college students from a Chinese university using the Impact of Event Scale-Revised (IES-R) and the Patient Health Questionnaire-9 (PHQ-9). A Gaussian Graphical Model (GGM) combined with graphical LASSO was used to construct the symptom network. Expected Influence (EI) was calculated to identify central symptoms, and Bridge Expected Influence (Bridge EI) was used to identify bridge symptoms connecting post-traumatic stress and depressive domains. Network accuracy and stability were examined using bootstrap procedures.

The symptom network revealed complex connectivity patterns among 31 symptom nodes. Central symptom analysis indicated that H2 (nervousness/exaggerated startle response, EI = 1.38), I4 (involuntary recall, EI = 1.33), and H4 (difficulty concentrating, EI = 1.09) exhibited the highest expected influence. Bridge symptom analysis showed that I8 (trauma-related dreams, Bridge EI = 0.88), H1 (irritability, Bridge EI = 0.85), and I7 (intense emotional fluctuations, Bridge EI = 0.80) were key bridges connecting the post-traumatic stress and depressive dimensions. The network demonstrated good stability, with a CS-coefficient of 0.75.

Nervousness/exaggerated startle response and involuntary recall are central symptoms in the post-traumatic stress-depression network among college students, while trauma-related dreams, irritability, and emotional fluctuations serve as key bridge symptoms connecting the two disorders. Clinical interventions should prioritize these hub symptoms to maximize treatment efficacy and disrupt cross-diagnostic symptom connectivity.