• Xiaoxuan Meng, Siyuan Li, Wenting Shen, Dongyan Li, Qingyun Lv, Xiaoxu Wang, Yan Wang, Xiaoying Zang, Qing Zhang, and Lan Wang.
• Nursing of School, Tianjin Medical University, Tianjin, China.
• Curr Med Res Opin. 2023 May 1; 39 (5): 671679671-679.

ObjectiveMany related scales have been developed and applied to measure patients' medication adherence, but the research on the psychometric characteristics of the scale still requires further studies. This study aims to provide further validation of the GMAS scale by using Rasch analysis and to make targeted recommendations for scale improvement.MethodsThis is a cross-sectional study using secondary data. 312 Chinese adult patients were recruited from two tertiary hospitals and one community health service center in Tianjin to complete a questionnaire containing the GMAS, from January to June 2020. Participants included to have at least one chronic condition and also have been on medication for more than 3 months, but excluded patients with major life-threatening illnesses (e.g. heart failure, cancer), cognitive impairments preventing clear expression and significant communication difficulties. Rasch analysis was used to explore the psychometric properties of the GMAS scale. Key indicators including unidimensionality, validity and reliability, differential item functioning and degree of fit with Rasch model are validated.ResultsAfter fitting the Rasch model for the first time, 56 samples poorly fitting the model were deleted. The remaining 256 samples were used for Rasch analysis. The results show that GMAS can fit the Rasch model well, which proves that the scale has favourable psychometric characteristics. But some items had differential item functioning in whether patients have comorbidities.ConclusionThe GMAS was found to be useful as a screening tool for patients' medication adherence problems reported, except some issues to be addressed for further improvement of the scale.

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