The Morisky Green Levine (MGL) adherence scale is a 4-item tool used for the detection of medication nonadherence among patients with chronic health conditions. Despite being widely used in Arabic-speaking research contexts, it has never been validated in Arabic language. The aim of this study was to translate and validate the MGL tool into Arabic. A standard forward-backward process was used to translate the questionnaire. Cronbach’s alpha coefficient was measured to assess internal consistency of the scale. The test-retest reliability measured the consistency of participants’ responses over time. Construct validity was evaluated by Explanatory factor analysis (EFA); Kaiser-Meyer-Olkin value and Bartlett’s test of sphericity were determined. Convergent validity was assessed using a preexisting medications Arabic Adherence Assessment Tool (AAAT). The model fit was evaluated using confirmatory factor analysis (CFA). Associations between the MGL scale scores and the patient demographic/clinical characteristics were tested by linear regressions. A total of 201 participants were included into the study. The MGL scale categorization revealed that 20.9%, 59.2% and 19.9% of the participants had high, moderate and low levels of adherence respectively. Adequate internal consistency (alpha = 0.593) was observed. A significant strong ICC and Pearson’s correlations were generated between responses at time 1 and time 2. EFA results elucidated the suitability of the data for factor analysis. Pearson’s coefficient (r) revealed a significant strong correlation between MGL scale and AAAT. CFA results confirmed a good fit for the suggested model. Linear regression revealed higher number of medications, more frequent outpatient clinic visits and not experiencing medication adverse effect factors significantly associated with better adherence. The Arabic version of MLG scale is a reliable valid tool to assess adherence among Arabic-speaking communities. Implementing interventions targeting patients not compliant to regular clinic visits and those at higher risk of experiencing medication side effects can greatly enhance medication adherence.
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