UNSW, Sydney, New South Wales, Australia.
UOW, Wollongong, New South Wales, Australia.
J Prim Care Community Health. 2020 Jan-Dec;11:2150132720974204. doi: 10.1177/2150132720974204.
This study aimed at assessing the self-management activities of type 2 diabetes patients using Structural Equation Modeling (SEM) which measures and analyzes the correlations between observed and latent variables. This statistical modeling technique explored the linear causal relationships among the variables and accounted for the measurement errors.
A sample of 200 patients was recruited from the middle-aged population of rural areas of Pakistan to explore the self-management activities of type 2 diabetes patients using the validated version of the Urdu Summary of Diabetes Self-care Activities (U-SDSCA) instrument. The structural modeling equations of self-management of diabetes were developed and used to analyze the variation in glycemic control (HbA1c).
The validated version of U-SDSCA instrument showed acceptable psychometric properties throughout a consecutive reliability and validity evaluation including: split-half reliability coefficient 0.90, test-retest reliability (r = 0.918, .001), intra-class coefficient (0.912) and Cronbach's alpha (0.79). The results of the analysis were statistically significant (α = 0.05, -value < .001), and showed that the model was very well fitted with the data, satisfying all the parameters of the model related to confirmatory factor analysis with chi-squared = 48.9, CFI = 0.94, TLI = 0.95, RMSEA = 0.065, SPMR = 0.068. The model was further improved once the items related to special diet were removed from the analysis, chi-squared value (30.895), model fit indices (CFI = 0.98, TLI = 0.989, RMSEA = 0.045, SPMR = 0.048). A negative correlation was observed between diabetes self-management and the variable HbA1c (r = -0.47; < .001).
The Urdu Summary of Diabetes Self-Care Activities (U-SDSCA) instrument was used for the patients of type 2 diabetes to assess their diabetes self-management activities. The structural equation models of self-management showed a very good fit to the data and provided excellent results which may be used in future for clinical assessments of patients with suboptimal diabetes outcomes or research on factors affecting the associations between self-management activities and glycemic control.
本研究旨在使用结构方程模型（SEM）评估 2 型糖尿病患者的自我管理活动，该模型可测量和分析观察变量和潜在变量之间的相关性。这种统计建模技术探索了变量之间的线性因果关系，并考虑了测量误差。
从巴基斯坦农村中年人群中招募了 200 名患者，使用经过验证的乌尔都语糖尿病自我护理活动摘要（U-SDSCA）量表评估 2 型糖尿病患者的自我管理活动。开发了糖尿病自我管理的结构建模方程，并用于分析血糖控制（HbA1c）的变化。
经过连续可靠性和有效性评估，验证后的 U-SDSCA 量表显示出可接受的心理测量特性，包括：半分可靠性系数 0.90、测试-重测信度（r=0.918，p<0.001）、内类系数（0.912）和 Cronbach 的 alpha 系数（0.79）。分析结果具有统计学意义（α=0.05，-值<.001），表明该模型与数据拟合得非常好，满足与验证性因子分析相关的所有模型参数，卡方值为 48.9，拟合度指数（CFI）为 0.94，TLI 为 0.95，RMSEA 为 0.065，SPMR 为 0.068。一旦将与特殊饮食相关的项目从分析中删除，模型进一步得到了改进，卡方值（30.895）、模型拟合指数（CFI=0.98，TLI=0.989，RMSEA=0.045，SPMR=0.048）。糖尿病自我管理与 HbA1c 变量呈负相关（r=-0.47；p<0.001）。
使用乌尔都语糖尿病自我护理活动摘要（U-SDSCA）量表评估 2 型糖尿病患者的糖尿病自我管理活动。自我管理的结构方程模型与数据拟合良好，提供了极佳的结果，可用于未来对血糖控制不理想的患者进行临床评估或对影响自我管理活动与血糖控制之间关联的因素进行研究。
