工作量-能力失衡及其对多重疾病患者自我管理复杂性的影响:一项多中心横断面研究。

Annals of medicine Pub Date : 2025-12-01 Epub Date: 2025-01-17 DOI:10.1080/07853890.2025.2451195
Binyu Zhao, Yujia Fu, Jingjie Wu, Erxu Xue, Chuyang Lai, Dandan Chen, Qiwei Wu, Jianing Yu, Qiaoyu Wu, Zhihong Ye, Jing Shao
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引用次数: 0

摘要

导言:多重疾病在全球范围内不断增加,强调需要有效的自我管理策略。累积复杂性模型(CuCoM)为理解基于工作负载和能力的自我管理提供了独特的视角。本研究旨在验证多病患者的CuCoM,并确定个性化的自我管理预测指标。方法:这项多中心横断面调查在中国5个初级卫生中心和4家医院招募了1920名多病患者。问卷评估了工作量(药物摄入、医生就诊和随访、生活中断和健康问题)、能力(社会、环境、财务、身体和心理)和自我管理。数据分析采用潜在剖面分析、卡方分析、多元线性回归和网络分析。结果:d患者分为低工作量-低容量(10.2%)、高工作量-低容量(7.5%)、低工作量-高容量(64.6%)和高工作量-高容量(17.7%)4种类型。低负荷、高负荷的患者自我管理能力较好(β = 0.271, p p p)。结论:提高负荷、减少负荷的个性化干预措施对改善多病患者的自我管理能力至关重要。促进卫生公平的上游政策对于取得更好的自我管理成果也至关重要。
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Workload-capacity imbalances and their impact on self-management complexity in patients with multimorbidity: a multicenter cross-sectional study.

Introduction: 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.

Methods: 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.

Results: 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, p < 0.001), while those with high workload and low capacity exhibited poorer self-management (β=-0.187, p < 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 (p < 0.05).

Conclusions: 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.

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