Objective  To explore the network structure of burnout and depressive symptoms among social workers and provide evidence for the construction of a precise symptom management program.

Methods  This study used baseline data from the China Social Work Longitudinal Study (CSWLS). The survey included basic information, burnout, and depressive symptoms. Regularized partial correlation network (R-PCN) and directed acyclic graph (DAG) were used to construct the network.

Results  A total of 6,448 social workers was included in the study. The detection rates of burnout and depressive symptoms were 32.04% and 21.00%, respectively. In the network of burnout and depressive symptom dimensions, the dimension with the highest expected influence (EI) was "emotional exhaustion", and the dimension with the highest bridge expected influence (BEI) was "interpersonal relationships". The symptom items exhibiting the highest EI in the depression and burnout network were CESD-19 (“I feel that people don't like me”) and B-7 (“I feel that my work is exhausting”); those with the highest BEI were CESD-20 (“I feel unable to continue living”) and B-9 (“I feel that service recipients will attribute the problems they should face to me”). The exploratory analysis of DAG suggested the conditional, directional, and dependent relationships between burnout and specific depressive dimensions (such as emotional exhaustion and depressive emotions, depersonalization and interpersonal relationships).

Conclusion  The network analysis of burnout and depressive symptoms among social workers shows that "emotional exhaustion" is the primary core node, and "interpersonal relationships" is the key bridging symptom. Close attention to these nodes may be crucial for preventing burnout and depression among social workers.

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