Symptom networks analysis among people with Meniere's disease: Application for nursing care

This study aimed to explore and visualize the relationships among multiple symptoms in patients with Meniere's disease (MD) and aid clinical nurses in the design of accurate, individualized interventions. This cross-sectional study included 790 patients with MD at the Eye and ENT Hospital of Fudan University from October 2014 to December 2021. A self-designed symptom checklist was used to assess 15 MD-related symptoms and construct contemporaneous networks with all 15 symptoms in R software. Qgraph package and Fruchterman-Reingold layout were used for network visualization. Bootstrapping methods were performed to assess network accuracy and stability, and three centrality indices were adopted to describe relationships among symptoms. "Anxiety and nervousness" was the most common symptom (98.2%) and "tinnitus" the most serious (1(1,3)). MD patients with long disease duration had high prevalence and severity for all symptoms. Symptom networks showed good accuracy and stability. "Decline in word recognition" was at the center of the symptom network. The ≥1-year disease group exhibited higher centralities for "drop attack" and "anxiety and nervousness," and a lower centrality for "headache" compared with the <1-year disease group. The symptom networks of MD patients with varying disease durations were revealed. Clinicians and nurses must provide precision interventions tailored to modifying symptom severity and centrality. Nursing interventions should focus on word recognition issues and associated discomfort in MD patients with multiple symptoms.