Network analysis of symptom burden and its influencing factors in first-ever subacute stroke patients
10.3761/j.issn.0254-1769.2025.07.004
- VernacularTitle:首发脑卒中恢复期患者症状负担及其影响因素的网络分析
- Author:
Kebing ZHOU
1
;
Xiaojiao HUANG
1
;
Fengxia YAN
1
Author Information
1. 510632 广州市 暨南大学护理学院
- Publication Type:Journal Article
- Keywords:
Stroke;
Symptom Burden;
Root Cause Analysis;
Network Analysis;
Nursing Care
- From:
Chinese Journal of Nursing
2025;60(7):792-798
- CountryChina
- Language:Chinese
-
Abstract:
Objective To explore the internal correlation mechanism among symptoms and influencing factors in first-ever subacute stroke patients.Methods A cross-sectional survey method was employed to conveniently select stroke patients hospitalized in a tertiary hospital in Guangdong Province from October 2022 to June 2023.Data were collected using a general information questionnaire,Symptom Experience Scale for Stroke Survivors,Fear of Progression Questionnaire-Short Form,Acceptance of Illness Scale,Herth Hope Index,and the Memorial University of Newfoundland Scale of Happiness.Results A total of 316 stroke patients were included.The incidence of symptom burden ranged from 17.41％to 87.97％,with the core,bridge,and sentinel symptoms as decreased attention and restricted limb movements,restricted limb movements and decreased self-care ability,and limb weakness and delayed response,respectively.Age,stroke type,disease stage,self-care ability,fear of disease progression,hope level,and happiness level were predictive factors for symptom burden in patients.Mixed network analysis showed direct correlation between foot inversion and stroke type,fear of disease progression was directly associated with limb weakness and limb pain.Low mood was directly correlated with hope level and happiness level.Conclusion Symptoms in patients with first-episode subacute stroke are interrelated.Nurses should pay attention to the identification of core,bridge,and sentinel symptoms,understand the associations between symptoms and influencing factors,and provide comprehensive and personalized clinical symptom management strategies for patients.
