用于药物坚持性研究的偏差风险工具:RoBIAS和RoBOAS
Klarissa A Sinnappah1, Dyfrig A Hughes2, Sophie L Stocker3,4,5
1School of Pharmacy, University of Otago, Dunedin, New Zealand.
British journal of clinical pharmacology
|January 21, 2025
概括
新的工具,干预依从性研究中的偏差风险工具 (RoBIAS) 和观察依从性研究中的偏差风险工具 (RoBOAS),帮助研究人员评估依从性研究中的偏差. 这些工具旨在提高证据的质量,并指导未来的研究设计.
科学领域:
- 医疗保健服务研究 医疗服务研究
- 临床研究方法论 临床研究方法论
- 制药科学 制药科学
背景情况:
- 准确的药物遵守文件对于质量研究和有针对性的干预措施至关重要.
- 缺乏现有的关于遵守性研究中偏见风险的指导.
- 需要开发标准化工具来解决这个差距.
研究的目的:
- 开发和评估工具,以识别和量化在坚持研究中的偏见.
- 为研究人员提供一种评估干预性和观察性依从性研究中偏差风险的手段.
- 提高坚持研究中证据的质量和可靠性.
主要方法:
- 开发了干预依从性研究中的偏差风险工具 (RoBIAS) 和观察依从性研究中的偏差风险工具 (RoBOAS).
- 工具的构建是基于对遵守指南的文献审查和专家共识.
- 工具草案由专家执法研究人员通过在线调查进行试点和评估.
主要成果:
- 这些工具围绕四个领域进行结构化:研究设计,随机化/混因素,依从性结果测量和数据分析.
- 每个领域包括对特定偏见进行映射的项目,这些偏见与坚持性研究相关.
- 一个基于域名的排名尺度有助于偏见判断的风险.
结论:
- 开发的工具 (RoBIAS和RoBOAS) 旨在对遵守研究进行系统审查.
- 这些工具可以为未来的依从性研究的设计提供信息.
- 这些工具的实施将提高坚持研究的严格性.
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