Association rules of social alienation in maintenance hemodialysis patients: an Apriori algorithm analysis and intervention strategies

维持性血液透析患者社会疏离的关联规则:基于Apriori算法的分析及干预策略

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Abstract

INTRODUCTION: Social alienation significantly impacts maintenance hemodialysis (MHD) patients. This study aimed to identify key factors associated with social alienation in MHD patients using association rule mining to inform interventions. METHODS: A cross-sectional study enrolled 250 MHD patients from 11 centers (March-April 2025). Social alienation was assessed using the General Alienation Scale (GAS). Sociodemographic, clinical, and treatment variables were analyzed using the Apriori algorithm with thresholds: support ≥ 30%, confidence ≥ 50%, lift > 1. RESULTS: Among participants, 49.2% (n = 123) reported social alienation. Seven strong association rules were identified. Key combinations included: Urban employee insurance + thrice-weekly dialysis (support 58.8%, confidence 54.4%); Male + urban employee insurance + thrice-weekly dialysis (support 36.8%, confidence 54.4%); Age 36-50 + Han ethnicity (support 31.2%, confidence 56.4%). A dialysis treatment plan of 4-5 h per week for three times, middle-aged working patients, and limited support were prominent risk factors. CONCLUSION: Social alienation in MHD patients is multifactorial. Interventions should include flexible dialysis scheduling, multidisciplinary psychosocial support, and community networks. Policy reforms addressing insurance-related employment stress are needed. Data-driven strategies enhance chronic disease management.

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