Work

Latent profile analysis and influencing factors for cluster of psychosomatic symptoms among chinese middle-aged and older ischemic stroke survivors

Year: 2025

Type: article

Abstract: BACKGROUND: A deeper understanding of individual differences in symptom experiences among middle-aged and older ischemic stroke survivors could enable healthcare professionals to identify previously unknown associations among complex symptoms. This study employs latent class analysis to characterize psychosocial symptom clusters in this population. By identifying distinct subgroups based on these clusters, we compare differences in their quality of life and identify key factors associated with this classification. The findings aim to establish a foundation for developing targeted symptom management models and tailored intervention strategies for stroke survivors. METHODS: A total of 350 middle-aged and older adult ischemic stroke survivors were recruited between September 2022 and September 2023. Psychosomatic symptom clusters, depressive symptoms, fatigue, pain, sleep quality, risk factors, and functional impairment were assessed using validated scales, including the Numerical Rating Scale, the Hospital Anxiety and Depression Scale, the Fatigue Severity Scale, the Self-Rating Scale of Sleep, the Self-Efficacy for Managing Chronic Disease Scale, the Perceived Social Support Scale, and the Stroke Impact Scale. RESULTS: The sample was classified into three subgroups: a "low symptom group" (71.4%, n=250), a "high anxiety-fatigue group" (12.6%, n=44), and a "high symptom group" (16.0%, n=56). Gender, age, post-stroke self-care ability, and NIHSS scores were significant predictors differentiating the latent classes of psychosomatic symptom clusters in this population of middle-aged and older ischemic stroke survivors. CONCLUSION: This study identified three distinct clusters of psychosomatic symptoms among middle-aged and older ischemic stroke survivors in China, the group with the highest symptoms had the poorest quality of life. The findings may assist clinical nurses in classifying high-risk patients for targeted psychosocial interventions, thereby offering a foundation for developing tailored clinical strategies.

Source: Geriatric Nursing

DOI: 10.1016/j.gerinurse.2025.103776

Authors: Jiayin Chen, Jiaxian Wang, Jiangnan Wei, Kezhou Yang, Bo Deng, Ning Liu

Institutions: Zunyi Medical University, Henan University of Science and Technology, First Affiliated Hospital of Henan University of Science and Technology, Foshan Hospital of TCM

Language: English

Topic: Stroke Rehabilitation and Recovery

Subfield: Rehabilitation

Field: Medicine

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: hybrid

Estimated APC paid: $3,280