Exploring Bridge Symptoms between Somatic Symptom Clusters and Anxiety and Depression Symptoms among Patients Recovering from Stroke: A Network Analysis
Yao Huang, Teng Li, Qian Yu, Suyao LiBackground:
Bridge symptoms connect different symptom clusters in a network and may serve as precise intervention targets. This study aimed to explore the bridge symptoms between somatic symptoms and anxiety and depressive symptoms among patients recovering from stroke using network analysis.
Methods:
A cross-sectional survey was conducted among 691 patients recovering from stroke who were recruited by convenience sampling from two tertiary hospitals. Symptom networks were estimated using the extended Bayesian information criterion (EBIC) graphical least absolute shrinkage and selection operator (GLASSO) method in R (qgraph package). The expected influence of the bridge was calculated to identify bridge symptoms, and network stability was assessed by bootstrapping (correlation stability [CS] coefficient). Anxiety and depressive symptoms were measured using the Hospital Anxiety and Depression Scale (HADS).
Results:
The symptom network demonstrated satisfactory stability (CS coefficient = 0.361 for bridge expected influence). The strongest edge was observed between HADS-A3 and HADS-D3 (
Conclusion:
Two bridge symptom pairs were identified in the stroke recovery network: HADS-A3/HADS-D3, bridging anxiety and depressive symptoms, and HADS-D6/HADS-A6, linking somatic symptoms with depressive and anxiety symptoms. These bridging nodes may serve as promising intervention targets to disrupt cross-cluster symptom propagation and reduce overall symptom burden.