Nursing of School, Tianjin Medical University, Tianjin, China.
Department of Health and Medical Services, Tianjin Medical University General Hospital, Tianjin, China.
Curr Med Res Opin. 2023 May;39(5):671-679. doi: 10.1080/03007995.2023.2196219. Epub 2023 Apr 8.
Many 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.
This 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.
After 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.
The 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.
已经开发并应用了许多相关的量表来衡量患者的用药依从性，但该量表的心理测量学特征仍需要进一步研究。本研究旨在通过使用 Rasch 分析进一步验证 GMAS 量表，并针对量表改进提出有针对性的建议。
这是一项使用二次数据的横断面研究。2020 年 1 月至 6 月，从天津市两家三级医院和一家社区卫生服务中心招募了 312 名中国成年患者，他们至少有一种慢性疾病，并且已经服用药物超过 3 个月，但排除了患有严重危及生命的疾病（如心力衰竭、癌症）、认知障碍导致无法清晰表达和严重沟通困难的患者。使用 Rasch 分析来探讨 GMAS 量表的心理测量特性。验证了关键指标，包括单维性、有效性和可靠性、区分项目功能和与 Rasch 模型的拟合程度。
首次拟合 Rasch 模型后，删除了 56 个拟合模型较差的样本。剩余的 256 个样本用于 Rasch 分析。结果表明，GMAS 可以很好地拟合 Rasch 模型，这证明该量表具有良好的心理测量特性。但有些项目在患者是否有合并症方面存在区分项目功能。
除了需要进一步改进量表外，GMAS 被发现是一种有用的工具，可以用来筛查患者报告的用药依从性问题。
