108985
论文已发表
注册即可获取德孚的最新动态
IF 收录期刊
- 3.4 Breast Cancer (Dove Med Press)
- 3.2 Clin Epidemiol
- 2.6 Cancer Manag Res
- 2.9 Infect Drug Resist
- 3.7 Clin Interv Aging
- 5.1 Drug Des Dev Ther
- 3.1 Int J Chronic Obstr
- 6.6 Int J Nanomed
- 2.6 Int J Women's Health
- 2.9 Neuropsych Dis Treat
- 2.8 OncoTargets Ther
- 2.0 Patient Prefer Adher
- 2.2 Ther Clin Risk Manag
- 2.5 J Pain Res
- 3.0 Diabet Metab Synd Ob
- 3.2 Psychol Res Behav Ma
- 3.4 Nat Sci Sleep
- 1.8 Pharmgenomics Pers Med
- 2.0 Risk Manag Healthc Policy
- 4.1 J Inflamm Res
- 2.0 Int J Gen Med
- 3.4 J Hepatocell Carcinoma
- 3.0 J Asthma Allergy
- 2.2 Clin Cosmet Investig Dermatol
- 2.4 J Multidiscip Healthc
已发表论文
脑卒中患者症状困扰与积极心理变量之间的关系：网络分析
Authors Zhuang S, Chen Y, Song Y, Qu Y, Zhang Y, Jin S, Lei F, Li L
Received 1 July 2025
Accepted for publication 14 October 2025
Published 22 October 2025 Volume 2025:18 Pages 6365—6375
DOI https://doi.org/10.2147/IJGM.S550771
Checked for plagiarism Yes
Review by Single anonymous peer review
Peer reviewer comments 2
Editor who approved publication: Dr Redoy Ranjan
Shumei Zhuang,1,* Yannan Chen,1,2,* Yuelin Song,1 Yitong Qu,1 Yinan Zhang,1 Shimei Jin,1 Fengjuan Lei,1 Lehan Li1
1School of Nursing, Tianjin Medical University, Tianjin, People’s Republic of China; 2Department of Cardiology, TEDA International Cardiovascular Hospital, Tianjin, People’s Republic of China
*These authors contributed equally to this work
Correspondence: Shumei Zhuang, School of Nursing, Tianjin Medical University, No. 22 Qixiangtai Road, Heping District, Tianjin, 300070, People’s Republic of China, Tel +86-13001378987, Email snshumei@126.com
Purpose: This study aims to investigate the topological structure of symptoms and positive psychological variables in stroke survivors through the network analysis method.
Patients and Methods: This is a cross-sectional study. A total of 622 Chinese stroke patients were recruited from six diverse tertiary general hospitals in Tianjin, China, from February to September 2024. The Assessment of Daily Living scale (ADL), Pittsburgh Sleep Quality Index (PSQI), Numerical Rating Scale (NRS), Mini-Mental State Examination (MMSE), Self-Rating Anxiety Scale (SAS), and Self-Rating Depression Scale (SDS) were employed to assess the distress caused by symptoms in these patients. Positive psychological constructs were quantified via the Herth Hope Index (HHI), Perceived Social Support Scale (PSSS), and General Self-Efficacy Scale (GSES). Network analysis was employed to investigate the interplay between these positive psychological variables and the distress associated with stroke symptoms.
Results: “Cognitive impairment’’ and “Functional disability” (MMSE-ADL, edge weight = − 0.610) had the strongest negative connection. “Anxiety” and “Depression” (SAS-SDS, edge weight = 0.556) had the strongest positive connection. Depression (SDS) demonstrated the highest strength centrality, indicating its role as the most interconnected symptom. Family support (PSSS-1) emerged as the most central positive psychology variable, with the highest closeness and betweenness scores, acting as a critical bridge between psychological and somatic symptom clusters.
Conclusion: Depression and family support are pivotal nodes in stroke symptom networks. Integrating family-centered interventions with early depression screening may disrupt symptom propagation and improve outcomes. These findings underscore the need for multicomponent strategies addressing both psychological and social determinants of recovery in stroke care.
Keywords: depression, network analysis, physical symptoms, positive psychology, stroke
1School of Nursing, Tianjin Medical University, Tianjin, People’s Republic of China; 2Department of Cardiology, TEDA International Cardiovascular Hospital, Tianjin, People’s Republic of China
*These authors contributed equally to this work
Correspondence: Shumei Zhuang, School of Nursing, Tianjin Medical University, No. 22 Qixiangtai Road, Heping District, Tianjin, 300070, People’s Republic of China, Tel +86-13001378987, Email snshumei@126.com
Purpose: This study aims to investigate the topological structure of symptoms and positive psychological variables in stroke survivors through the network analysis method.
Patients and Methods: This is a cross-sectional study. A total of 622 Chinese stroke patients were recruited from six diverse tertiary general hospitals in Tianjin, China, from February to September 2024. The Assessment of Daily Living scale (ADL), Pittsburgh Sleep Quality Index (PSQI), Numerical Rating Scale (NRS), Mini-Mental State Examination (MMSE), Self-Rating Anxiety Scale (SAS), and Self-Rating Depression Scale (SDS) were employed to assess the distress caused by symptoms in these patients. Positive psychological constructs were quantified via the Herth Hope Index (HHI), Perceived Social Support Scale (PSSS), and General Self-Efficacy Scale (GSES). Network analysis was employed to investigate the interplay between these positive psychological variables and the distress associated with stroke symptoms.
Results: “Cognitive impairment’’ and “Functional disability” (MMSE-ADL, edge weight = − 0.610) had the strongest negative connection. “Anxiety” and “Depression” (SAS-SDS, edge weight = 0.556) had the strongest positive connection. Depression (SDS) demonstrated the highest strength centrality, indicating its role as the most interconnected symptom. Family support (PSSS-1) emerged as the most central positive psychology variable, with the highest closeness and betweenness scores, acting as a critical bridge between psychological and somatic symptom clusters.
Conclusion: Depression and family support are pivotal nodes in stroke symptom networks. Integrating family-centered interventions with early depression screening may disrupt symptom propagation and improve outcomes. These findings underscore the need for multicomponent strategies addressing both psychological and social determinants of recovery in stroke care.
Keywords: depression, network analysis, physical symptoms, positive psychology, stroke