Classifying self‐management clusters of patients with mild cognitive impairment associated with diabetes: A cross‐sectional study

横断面研究 共病 医学 糖尿病 描述性统计 星团(航天器) 多级模型 自我管理 聚类分析 疾病 临床心理学 心理学 精神科 内科学 人工智能 病理 计算机科学 数学 程序设计语言 统计 内分泌学 机器学习
作者
Wang Yunxian,Yuan‐Jiao Yan,Rong Lin,Jing Liang,Na‐Fang Wang,Mingfeng Chen,Hong Li
出处
期刊:Journal of Clinical Nursing [Wiley]
卷期号:33 (3): 1209-1218
标识
DOI:10.1111/jocn.16993
摘要

This study aims to propose a self-management clusters classification method to determine the self-management ability of elderly patients with mild cognitive impairment (MCI) associated with diabetes mellitus (DM).MCI associated with DM is a common chronic disease in old adults. Self-management affects the disease progression of patients to a large extent. However, the comorbidity and patients' self-management ability are heterogeneous.A cross-sectional study based on cluster analysis is designed in this paper.The study included 235 participants. The diabetes self-management scale is used to evaluate the self-management ability of patients. SPSS 21.0 was used to analyse the data, including descriptive statistics, agglomerative hierarchical clustering with Ward's method before k-means clustering, k-means clustering analysis, analysis of variance and chi-square test.Three clusters of self-management styles were classified as follows: Disease neglect type, life oriented type and medical dependence type. Among all participants, the percentages of the three clusters above are 9.78%, 32.77% and 57.45%, respectively. The difference between the six dimensions of each cluster is statistically significant.This study classified three groups of self-management styles, and each group has its own self-management characteristics. The characteristics of the three clusters may help to provide personalized self-management strategies and delay the disease progression of MCI associated with DM patients.Typological methods can be used to discover the characteristics of patient clusters and provide personalized care to improve the efficiency of patient self-management to delay the progress of the disease.In our study, we invited patients and members of the public to participate in the research survey and conducted data collection.
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