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Mapping the Symptom Networks of Depression, Anxiety, and Their Comorbidity Among Chinese Individuals Under Community
Yichao Lv1,2, Ruyong Li3, Zhe Hou4
1Faculty of Psychology, Beijing Normal University, Beijing, China.
Objective:
Individuals under community correction are a high-risk population for anxiety and depression, which frequently co-occur. However, the symptom network structures of anxiety, depression, and their comorbidity in this population remained unexplored. This study addresses this gap using a network analysis approach.
Methods:
A total of 818 Chinese individuals under community correction (134 females, 684 males; over 95% aged 18-60 years) completed the Self-Rating Anxiety Scale (SAS) and Self-Rating Depression Scale (SDS). Separate symptom networks for anxiety and depression were estimated to identify central symptoms using expected influence (EI), while a comorbidity network was estimated to identify bridge symptoms using bridge EI and bridge betweenness. Directed acyclic graph (DAG) analyses were then conducted to identify potential trigger symptoms and further clarify the roles of central and bridge symptoms.
Results:
A total of 36.7% and 13.1% of participants reported depression and anxiety symptoms, respectively, with 11.0% exhibiting comorbidity. In the anxiety network, "panic" (SAS-03) was the central symptom (highest EI) and the key trigger symptom in the DAG. In the depression network, "emptiness" (SDS-18) was the central symptom, while "fatigue" (SDS-10) was the key trigger. In the comorbidity network, "insomnia" (SAS-19), "sleep disturbance" (SDS-04), and "fatigue" were identified as bridge symptoms. In the comorbidity DAG, "fatigue" acted as a key trigger, facilitating the transmission from depression to anxiety via "sleep disturbance" and "insomnia."
Conclusion:
The study preliminarily examined the phenomenon and mechanisms of anxiety, depression, and their comorbidity among individuals under community correction, providing new insights for intervention planning.
