Skip to content
naulon
Not checkedNot checked for notices yet.

Psychometric Properties of Persian Version of the 8-item Morisky Medication Adherence Scale in Type 2 Diabetes Patients

Mehran Nakhaeizadeh, Ali Khalooei

Journal of Clinical and Diagnostic Research · 2019

doi:10.7860/jcdr/2019/41408.13076 (opens in a new tab)

We email you when a new notice or a question about this paper appears.

Abstract

Introduction: The 8-items Morisky Medication Adherence Scale (MMAS-8) is a brief questionnaire that is applied to assess medication-taking behaviours. Aim: To evaluate the validity and reliability of the Persian version of MMAS-8 among Type 2 Diabetes Mellitus (T2DM) patients in Iran. Materials and Methods: A cross-sectional study was conducted among 589 T2DM patients in Kerman city (southeast Iran) from January to March 2017. Data were collected using MMAS-8 and diabetes self-management questionnaires. To check test re-test reliability and to determine the internal consistency Intra-class Correlation Coefficient (ICC) and Cronbach’s alpha method were employed. Also, convergent validity was assessed by correlation analysis method. Results: Cronbach’s alpha and ICC of MMAS-8 were 0.75 and 0.88, respectively. The correlation coefficient between MMAS-8 and medication adherence subscale of diabetes selfmanagement questionnaire was 0.85 (p<0.001). Exploratory Factor Analysis (EFA) showed two factors for MMAS-8. The first factor included items 1, 2, 3, 4, 6, and 8. Moreover, items 5 and 7 fell in the second factor. Confirmatory Factor Analysis (CFA) indices for modified MMAS-8 without Items 5 and 7 model (X2=9.3, DF=6, P=0.15, CFI=0.99, RMSEA=0.04, TLI=0.98, and NFI=0.98) were acceptable. Conclusion: In this study, the Persian version of MMAS-8 was investigated to find out whether it is a reliable and valid scale for assessing medication-taking behaviours in T2DM patients. The results showed that it can be applied for Iranian diabetic patients by health care providers and researchers.

Abstract licence: CC BY-NC-ND

Reads

Read by people on this page

None yet.

Checked or read by AI through naulon

None yet.

A person counts once a day per paper. We keep no cookie and no address: a reader is a hash that changes every day. Any month under five reads shows no number.

Are you an author?

Is this your paper?

Claim it to add your note and be paid when agents cite it. Free.