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识别成年人的糖尿病自我管理特征:使用选定的自我报告结果进行聚类分析。

Identification of diabetes self-management profiles in adults: A cluster analysis using selected self-reported outcomes.

机构信息

School of Health Sciences (HESAV), University of Applied Sciences and Arts Western Switzerland (HES-SO), Lausanne, Switzerland.

Center for Primary Care and Public Health (Unisanté), University of Lausanne, Lausanne, Switzerland.

出版信息

PLoS One. 2021 Jan 22;16(1):e0245721. doi: 10.1371/journal.pone.0245721. eCollection 2021.

Abstract

The present study describes adult diabetes self-management (DSM) profiles using self-reported outcomes associated with the engagement in diabetes care activities and psychological adjustment to the disease. We used self-reported data from a community-based cohort of adults with diabetes (N = 316) and conducted a cluster analysis of selected self-reported DSM outcomes (i.e., DSM behaviors, self-efficacy and perceived empowerment, diabetes distress and quality of life). We tested whether clusters differed according to sociodemographic, clinical, and care delivery processes variables. Cluster analysis revealed four distinct DSM profiles that combined high/low levels of engagement in diabetes care activities and good/poor psychological adjustment to the disease. The profiles were differently associated with the variables of perceived financial insecurity, taking insulin treatment, having depression, and the congruence of the care received with the Chronic Care Model. The results could help health professionals gain a better understanding of the different realities facing people living with diabetes, identify patients at risk of poor outcomes related to their DSM, and lead to the development of profile-specific DSM interventions.

摘要

本研究使用与参与糖尿病护理活动和对疾病的心理适应相关的自我报告结果,描述了成年人的糖尿病自我管理(DSM)特征。我们使用来自基于社区的成年人糖尿病队列的自我报告数据(N=316),并对选定的自我报告 DSM 结果(即 DSM 行为、自我效能感和感知赋权、糖尿病困扰和生活质量)进行了聚类分析。我们测试了聚类是否根据社会人口统计学、临床和护理提供过程变量而有所不同。聚类分析显示了四种不同的 DSM 特征,这些特征结合了高水平/低水平的参与糖尿病护理活动和良好/较差的疾病心理适应。这些特征与感知财务不安全、使用胰岛素治疗、抑郁以及所接受的护理与慢性护理模式的一致性等变量存在不同程度的关联。研究结果可以帮助卫生专业人员更好地了解糖尿病患者所面临的不同现实情况,识别与他们的 DSM 相关的不良结局风险较高的患者,并针对特定的 DSM 干预措施进行个性化的干预。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0631/7822269/b2065159d4f8/pone.0245721.g001.jpg

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