ArticleJournal of research in pharmacy practice2026
Assessment of Psychometric Properties of the Persian Version of the Medication Literacy Measure.
Article in Journal of research in pharmacy practice, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Objective: Given the association between medication literacy (ML) and its correct use, assessing the status of ML is essential in the community. This study aimed to validate a Persian-language ML assessment instrument, addressing the lack of a previously validated Persian tool. Methods: This was a cross-sectional study conducted in Tehran. A database search was conducted to identify current tools. The selected instrument was translated and then back-translated into English. Questions regarding medication information-seeking behaviors and attitudes toward pharmacist guidance were added. The instrument was presented to the Academy of Medical Sciences, and their feedback was incorporated. The content validity index (CVI), content validity ratio (CVR), and comprehensiveness were assessed based on the experts. Reliability was evaluated through test-retest (intraclass correlation coefficient [ICC]) and internal consistency (Kuder-Richardson [KR] coefficient). Findings: Two systematic reviews that evaluated 52 ML tools were assessed. ML measure (MLM-17) was selected. Four questions on attitudes and behaviors were added. Following feedback from the academy, the number of these questions increased to 7, while one ML question was replaced. Following the experts' comments, a CVI of 0.77 was calculated, and questions with a CVR <0.99 were revised or removed. Accordingly, two questions were removed from the attitude and behavior sections, and one question was added to the ML section. The assessment of reliability showed ICC = 0.67 and KR = 0.71. Conclusions: The psychometric evaluation confirmed the tool's validity and reliability. Therefore, it is a suitable instrument for assessing ML in Persian-speaking populations.
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