Evidence map›Paper›PMID 40294004›Full record

ArticlePloS one2025

Cross-cultural adaptation and psychometric evaluation of the urdu version of the morisky, greene, and levine medication adherence scale (MGLS-4) for major depressive disorder patients.

Sohail Riaz, Fazli Khuda, Nadia Shamshad Malik, Nitasha Gohar, Ayesha Rashid, Abuzar Khan, Abdur Rahman, Sajid Ali, Asif Jan, Aqeel Nasim

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Article in PloS one, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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5 · Who and what money

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10 authors.

Sohail RiazDepartment of Pharmacy, University of Peshawar, Peshawar, Pakistan.ORCID 0000-0002-4188-5162
Fazli KhudaDepartment of Pharmacy, University of Peshawar, Peshawar, Pakistan.ORCID 0000-0002-6847-1744
Nadia Shamshad MalikFaculty of Pharmacy, Capital University of Science and Technology, Islamabad, Pakistan.
Nitasha GoharFaculty of Pharmacy, Capital University of Science and Technology, Islamabad, Pakistan.
Ayesha RashidDepartment of Pharmacy, The Women University Multan, Multan, Pakistan.
Abuzar KhanDepartment of Pharmacy, University of Peshawar, Peshawar, Pakistan.
Abdur RahmanDepartment of Psychology, International Islamic University, Islamabad, Pakistan.
Sajid AliDepartment of Biotechnology, Abdul Wali Khan University, Mardan, Pakistan.
Asif JanDepartment of Pharmacy, University of Peshawar, Peshawar, Pakistan.
Aqeel NasimBalochistan Institute of Nephrology Urology Quetta BINUQ, Quetta, Pakistan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In Pakistan, Major depressive disorder (MDD) contributes significantly to the mental health burden. It is crucial to understand patients' medication adherence status for developing a strategy for improving adherence and treatment outcomes. Therefore, a valid and reliable tool in the local Urdu language is required. The Morisky, Greene, and Levine Medication Adherence Scale (MGLS-4) is a reliable, valid and straightforward instrument to assess medication-taking behavior. The valid and reliable Urdu translation of MGLS-4 can fill this gap within the local context. Therefore, the present study aims to validate the Urdu Morisky, Green and Levine Adherence Scale (UMGLS-4) for MDD patients. This was a quantitative, cross-sectional validation study for Pakistani MDD patients. Reliability was measured using Cronbach's α and for test-retest reliability intraclass correlation coefficient (ICC) was calculated. Validity was assessed through face validity, content validity, construct validity, and convergent validity with the Drug Attitude Inventory (DAI-10). Descriptive and inferential statistical analyses were carried out to demonstrate adherence level and statistical significance, respectively. Linear regression was applied to find the association between the UGMLS-4 score and demographic characteristics. The UMGLS-4 demonstrated high reliability (Cronbach's α = 0.829) and a significant strong ICC (x = 0.601, p < 0.01) was detected. Exploratory factor analysis (EFA) revealed a single-factor structure explaining 66.084% of the variance. Confirmatory factor analysis (CFA) confirmed good model fit (GFI = 0.950, AGFI = 0.920, NFI = 0.930, RMSEA = 0.050, SRMSR = 0.055). Medication adherence was observed to be high in 39.1% of patients, moderate in 28.6%, and poor in 32.3%. Significant associations were found between adherence scores and gender, educational attainment, and occupational status (p < 0.005) with education predicting adherence (B = 0.301, p < 0.000), indicating the scale's robustness in detecting adherence variations among Urdu-speaking MDD patients. The UMGLS-4 is a reliable and valid tool for assessing medication adherence in Pakistani MDD patients, effectively capturing adherence variations across demographic variables.

Indexed as

Major Depressive DisorderMedication AdherencePsychometricsAdultCross-Cultural ComparisonCross-Sectional StudiesFemaleHumansLanguageMaleMiddle AgedPakistanReproducibility of ResultsSurveys and QuestionnairesYoung Adult

Identifiers

PMID40294004
PMCPMC12036920

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