1. Benefit finding in individuals undergoing maintenance hemodialysis in Shanghai: a latent profile analysis.
- Author
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Jie Yang, Yong-qi Li, Yan-lin Gong, Hong-li Yan, Jing Chen, Ling-ling Liu, Jing Wu, and Jing Chu
- Subjects
MULTIPLE regression analysis ,REGRESSION analysis ,SOCIAL support ,ANALYSIS of variance - Abstract
Objective: This multi-center cross-sectional study aimed to delineate latent profiles of benefit finding (BF) in individuals undergoing maintenance hemodialysis (MHD) in Shanghai and examine associations between these BF profiles, social support, and coping style. Methods: A total of 384 individuals undergoing MHD (mean age = 57.90, SD = 13.36) were assessed using the Benefit Finding Scale, Simplified Coping Style Questionnaire, and Perceived Social Support Scale. Latent profile analysis (LPA) identified distinct BF categories. Analysis of variance (ANOVA) evaluated the correlation between BF groups and demographic variables, while the relationship between BF, social support, and coping style was tested through correlation and multiple regression analyses. Results: LPA identified three BF groups: rich BF (54.17%), moderate BF (41.14%), and poor BF (4.69%). Regression analyses indicated that positive coping and social support are protective factors for BF. Additionally, older age and heightened understanding of MHD correlated with higher BF levels. Conclusion: The findings highlighted the importance of recognizing different BF profiles in individuals on MHD and working toward promoting BF levels in the rich BF and moderate BF groups, while helping the poor BF group to identify and address their challenges. Medical professionals should consider interventions tailored to individual psychological profiles to improve mental health and quality of life outcomes in this population. [ABSTRACT FROM AUTHOR]
- Published
- 2024
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