Zhao Binyu, Fu Yujia, Wu Jingjie, Xue Erxu, Lai Chuyang, Chen Dandan, Wu Qiwei, Yu Jianing, Wu Qiaoyu, Ye Zhihong, Shao Jing
Department of Nursing, The Fourth Affiliated Hospital of School of Medicine, and International School of Medicine, International Institutes of Medicine, Zhejiang University, Yiwu, Zhejiang, China.
School of Nursing and Institute of Nursing Research, School of Medicine, Zhejiang University, Hangzhou, Zhejiang, China.
Ann Med. 2025 Dec;57(1):2451195. doi: 10.1080/07853890.2025.2451195. Epub 2025 Jan 17.
Multimorbidity is increasing globally, emphasizing the need for effective self-management strategies. The Cumulative Complexity Model (CuCoM) offers a unique perspective on understanding self-management based on workload and capacity. This study aims to validate the CuCoM in multimorbid patients and identify tailored predictors of self-management.
This multicenter cross-sectional survey recruited 1920 multimorbid patients in five primary health centres and four hospitals in China. The questionnaire assessed workload (drug intake, doctor visits and follow-up, disruption in life, and health problems), capacity (social, environmental, financial, physical, and psychological), and self-management. Data were analyzed using latent profile analysis, chi-square, multivariate linear regression, and network analysis.
d Patients were classified into four profiles: low workload-low capacity (10.2%), high workload-low capacity (7.5%), low workload-high capacity (64.6%), and high workload-high capacity (17.7%). Patients with low workload and high capacity exhibited better self-management (β = 0.271, < 0.001), while those with high workload and low capacity exhibited poorer self-management (β=-0.187, < 0.001). Social capacity was the strongest predictor for all profiles. Environmental capacity ranked second for 'high workload-high capacity' (R² = 3.26) and 'low workload-low capacity' (R² = 5.32) profiles. Financial capacity followed for the 'low workload-high capacity' profile (R² = 5.40), while psychological capacity was key in the 'high workload-low capacity' profile (R² = 6.40). In the network analysis, socioeconomic factors exhibited the central nodes ( < 0.05).
Personalized interventions designed to increase capacity and reduce workload are essential for improving self-management in multimorbid patients. Upstream policies promoting health equity are also crucial for better self-management outcomes.
全球范围内，多种疾病并存的情况日益增多，这凸显了有效自我管理策略的必要性。累积复杂性模型（CuCoM）为基于工作量和能力理解自我管理提供了独特视角。本研究旨在验证CuCoM在患有多种疾病的患者中的有效性，并确定自我管理的个性化预测因素。
这项多中心横断面调查在中国的五个基层医疗中心和四家医院招募了1920名患有多种疾病的患者。问卷评估了工作量（药物摄入、看医生和随访、生活干扰以及健康问题）、能力（社会、环境、经济、身体和心理方面）以及自我管理情况。使用潜在类别分析、卡方检验、多元线性回归和网络分析对数据进行分析。
患者被分为四种类型：低工作量 - 低能力（10.2%）、高工作量 - 低能力（7.5%）、低工作量 - 高能力（64.6%）和高工作量 - 高能力（17.7%）。工作量低且能力高的患者表现出更好的自我管理能力（β = 0.271，< 0.001），而工作量高且能力低的患者自我管理能力较差（β = -0.187，< 0.001）。社会能力是所有类型患者中最强的预测因素。环境能力在“高工作量 - 高能力”（R² = 3.26）和“低工作量 - 低能力”（R² = 5.32）类型中排名第二。经济能力在“低工作量 - 高能力”类型中紧随其后（R² = 5.40），而心理能力在“高工作量 - 低能力”类型中是关键因素（R² = 6.40）。在网络分析中，社会经济因素呈现为中心节点（< 0.05）。
旨在提高能力和减少工作量的个性化干预措施对于改善患有多种疾病患者的自我管理至关重要。促进健康公平的上游政策对于取得更好的自我管理效果也至关重要。
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