Relationships Between Symptom Distress and Positive Psychological Variables Among Stroke Patients: A Network Analysis.

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.