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中文版8条目Morisky服药依从性量表在2型糖尿病患者中的信效度评价及应用研究 被引量:121

Reliability and validity of Chinese version of 8-item Morisky medication adherence scale in patients with type 2 diabetes
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摘要 目的评价中文版8条目Morisky服药依从性量表(MMAS-8)在2型糖尿病患者中应用的信度、效度,探讨不同因素对患者服药依从性的影响。方法选取2014年7月至2015年1月就诊于昆明医科大学第一附属医院的148例2型糖尿病患者,进行中文版MMAS-8及4条目Morisky服药依从性量表(MMAS-4)的调查。对中文版MMAS-8,选用Cronbach′sα系数评价其内部一致性信度,选用组内相关系数(ICC)评价重测信度;采用主成分因子分析法评价结构效度,采用Spearman相关系数评价聚合效度。对血糖达标组与血糖未达标组中文版MMAS-8得分采用两独立样本t检验进行比较,对血糖达标组与血糖未达标组服药依从性分布采用χ~2检验进行比较,评价中文版MMAS-8区分效度。对2型糖尿病患者服药依从性影响因素采用多因素有序多分类logistic回归方法进行分析。结果中文版MMAS-8的Cronbach′sα系数为0.776,ICC为0.854(P <0.05);主成分因子分析法共提取3个公因子;MMAS-8与MMAS-4评分的相关系数为0.878(P <0.001);血糖达标组(糖化血红蛋白<7%)MMAS-8得分高于血糖未达标组(糖化血红蛋白≥7%),差异具有统计学意义[(7.20±1.04)vs(5.94±2.03),t=3.910,P <0.001],两组间低、中等、高依从性分布比较,差异有统计学意义(χ~2=14.554,P=0.010)。影响2型糖尿病患者服药依从性的多因素有序多分类logistic回归分析提示:男性患者较女性患者服药依从性低(OR=0.405,95%CI=0.197~0.829,P=0.013);职工医保患者较自费患者服药依从性低(OR=0.130,95%CI=0.021~0.800,P=0.028);单药治疗较联合治疗患者依从性高(OR=2.970,95%CI=1.499~5.882,P=0.002)。年龄、病程、学历、职业、BMI、并发症、合并症、胰岛素治疗与否对服药依从性无显著影响,差异无统计学意义(P均> 0.05)。结论中文版MMAS-8具有良好的信度、效度;2型糖尿病患者的服药依从性与性别、医保类型及降糖方案有关。 Objective To evaluate the reliability and validity of the Chinese version of the 8-item Morisky medication adherence scale(MMAS-8)in patients with type 2 diabetes and to explore the influence of different factors on patient medication compliance.Methods We used the Chinese version of MMAS-8 and MMAS-4 to survey 148 type 2 diabetes patients who were treated at the First Affiliated Hospital of Kunming Medical University from July 2014 to January 2015.For the Chinese version of MMAS-8,we used Cronbach's alpha to evaluate its internal consistency reliability,and intra-group correlation coefficient(ICC)to evaluate the test-retest reliability;we also used principal component factor analysis to evaluate construct validity and Spearman correlation coefficient to evaluate the convergent validity.Two independent sample t-tests were used to compare the scores of the Chinese version of MMAS-8 in patients with good glycemic control and those with poor glycemic control,and the chi-square test was used to compare the distribution of drug adherence in patients with good glycemic control and those with poor glycemic control,in order to evaluate discriminant validity of the Chinese version of MMAS-8.Multivariate logistic regression analysis was used to analyze the influencing factors of drug adherence in type 2 diabetes patients.Results The Cronbach's alpha of the Chinese version of the MMAS-8 was 0.776,and the ICC was 0.854(P<0.05).Principal component factor analysis extracted three common factors.The correlation coefficient between the MMAS-8 and MMAS-4 was 0.878(P<0.001).The MMAS-8 score was significantly higher in patients with good glycemic control(HbA1c<7%)than in those with poor glycemic control(HbA1c ≥ 7%)[(7.20±1.04)vs(5.94±2.03),t=3.910,P<0.001],and the distribution of patients with different compliance also differed significantly between the two groups(χ^2=14.554,P=0.010).Multivariate logistic regression analysis showed that men compared to women(OR=0.405,95%CI=0.197-0.829,P=0.013),medical insurance for urban workers compared to self-paying(OR=0.130,95%CI=0.021-0.800,P=0.028),and monotherapy compared to multi-drug treatment(OR=2.970,95%CI=1.499-5.882,P=0.002)had a significant effect on medication adherence.Age,course of disease,education,occupation,body mass index,complications,and insulin treatment had no significant effect on medication compliance(P>0.05).Conclusion The Chinese version of the MMAS-8 has good reliability and validity.The medication adherence of patients with type 2 diabetes is associated with gender,the type of medical insurance,and hypoglycemic therapy.
作者 翁艳君 赵豫梅 刘伟军 宋滇平 Weng Yanjun;Zhao Yumei;Liu Weijun;Song Dianping(Department of Diabetes,the First Affiliated Hospital of Kunming Medical University,Kunming 650032,China)
出处 《中华临床医师杂志(电子版)》 CAS 2018年第8期445-450,共6页 Chinese Journal of Clinicians(Electronic Edition)
关键词 糖尿病 服药依从性 8条目Morisky服药依从性量表 影响因素 Diabetes Medication compliance 8-item Morisky medication adherence scale Influencing factor
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