학술논문

Symptom networks analysis among people with Meniere’s disease: Application for nursing care
Document Type
article
Source
International Journal of Nursing Sciences, Vol 11, Iss 2, Pp 214-221 (2024)
Subject
Meniere’s disease
Network analysis
Nurses
Patients
Syndrome
Nursing
RT1-120
Language
English
ISSN
2352-0132
Abstract
Objectives: 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. Methods: This 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. Results: Symptom networks showed good accuracy and stability. “Anxiety and nervousness”(98.2%), “aural fullness”(84.4%) and “tinnitus”(82.7%) were the common symptom in MD patients, while “tinnitus”, “aural fullness” and “decline in word recognition”, were more serious. MD patients with longer disease duration had higher prevalence and severity for all symptoms (P < 0.05). Symptom networks showed good accuracy and stability. “Decline in word recognition,” “fatigue,” and “anxiety and nervousness” were at the center of the symptom networks, which had the largest strength values and closeness. “Decline in word recognition,” “headache,” and “spatial discrimination and poor orientation” were the symptoms with the highest betweenness with the strongest bridging effect. The ≥1-year disease group exhibited higher centralities for “drop attack” and “anxiety and nervousness,” and a lower centrality for “headache” compared with the