Journal of psychosomatic research · 2026
The interplay between benefit finding and quality of life in maintenance hemodialysis patients: A cross-sectional network analysis.
СтатьяНазвание и аннотация: Перевод в очереди
Обработка статьи · этапы, ошибки и управление
Загрузка состояния…
Ошибки и ограничения
История · было → стало
Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.
Zhou Shuang, Tian Zhiwu, Wu Qin, Li Fuzhen, Tao Hongmei, Mai Meifang, Zhang Meifen
Аннотация
OBJECTIVE: Maintenance hemodialysis (MHD) patients experience significant impacts on their quality of life (QoL). Benefit finding (BF) may influence QoL, but the specific structural relationships between BF dimensions and QoL domains remain unclear. The aim of this study was to identify core components of BF and QoL networks and bridging pathways linking them in MHD patients.
METHODS: A cross-sectional study was conducted among 290 MHD patients from a tertiary hospital in China (January-June 2021). BF was assessed using the 22-item Benefit Finding Scale, and QoL was measured with the KDQOL-36™. Network analysis was employed to construct the BF-QoL network, estimate node centrality (strength, closeness, betweenness), and identify bridge connections. Stability was assessed using bootstrap methods (1000 samples).
RESULTS: The BF network identified Personal Growth (strength = 2.367) as the most central node. In the QoL network, Effects of Kidney Disease (strength = 0.558) was central. Between-network analysis revealed Acceptance and Mental Composite Score as critical bridge nodes (highest betweenness: 1.592 and 1.298, respectively). Significant edges connected Acceptance to Mental Composite Score (r = 0.134, P < 0.05) and Health Behaviors to Physical Composite Score (r = 0.119, P < 0.05). Network sparsity was 0.4. Centrality stability was robust (correlation-stability coefficient > 0.5 for strength/closeness).
CONCLUSION: BF and QoL form an interconnected network in MHD patients. Personal Growth and Effects of Kidney Disease are central to their respective constructs, while Acceptance and mental health bridge BF and QoL. Interventions targeting these core nodes may optimize multidimensional QoL outcomes.
METHODS: A cross-sectional study was conducted among 290 MHD patients from a tertiary hospital in China (January-June 2021). BF was assessed using the 22-item Benefit Finding Scale, and QoL was measured with the KDQOL-36™. Network analysis was employed to construct the BF-QoL network, estimate node centrality (strength, closeness, betweenness), and identify bridge connections. Stability was assessed using bootstrap methods (1000 samples).
RESULTS: The BF network identified Personal Growth (strength = 2.367) as the most central node. In the QoL network, Effects of Kidney Disease (strength = 0.558) was central. Between-network analysis revealed Acceptance and Mental Composite Score as critical bridge nodes (highest betweenness: 1.592 and 1.298, respectively). Significant edges connected Acceptance to Mental Composite Score (r = 0.134, P < 0.05) and Health Behaviors to Physical Composite Score (r = 0.119, P < 0.05). Network sparsity was 0.4. Centrality stability was robust (correlation-stability coefficient > 0.5 for strength/closeness).
CONCLUSION: BF and QoL form an interconnected network in MHD patients. Personal Growth and Effects of Kidney Disease are central to their respective constructs, while Acceptance and mental health bridge BF and QoL. Interventions targeting these core nodes may optimize multidimensional QoL outcomes.