Center for Addiction Medicine, Recovery Research Institute, Massachusetts General Hospital & Harvard Medical School, Boston, MA, USA.
Institute for Collaboration On Health, Intervention, Department of Psychological Sciences, University of Connecticut & Policy, Mansfield, USA.
Prev Sci. 2022 Jul;23(5):809-820. doi: 10.1007/s11121-021-01279-8. Epub 2021 Jul 21.
When seeking to inform and improve prevention efforts and policy, it is important to be able to robustly synthesize all available evidence. But evidence sources are often large and heterogeneous, so understanding what works, for whom, and in what contexts can only be achieved through a systematic and comprehensive synthesis of evidence. Many barriers impede comprehensive evidence synthesis, which leads to uncertainty about the generalizability of intervention effectiveness, including inaccurate titles/abstracts/keywords terminology (hampering literature search efforts), ambiguous reporting of study methods (resulting in inaccurate assessments of study rigor), and poorly reported participant characteristics, outcomes, and key variables (obstructing the calculation of an overall effect or the examination of effect modifiers). To address these issues and improve the reach of primary studies through their inclusion in evidence syntheses, we provide a set of practical guidelines to help prevention scientists prepare synthesis-ready research. We use a recent mindfulness trial as an empirical example to ground the discussion and demonstrate ways to ensure the following: (1) primary studies are discoverable; (2) the types of data needed for synthesis are present; and (3) these data are readily synthesizable. We highlight several tools and practices that can aid authors in these efforts, such as using a data-driven approach for crafting titles, abstracts, and keywords or by creating a repository for each project to host all study-related data files. We also provide step-by-step guidance and software suggestions for standardizing data design and public archiving to facilitate synthesis-ready research.
当寻求提供信息和改进预防措施和政策时,能够强有力地综合所有可用证据非常重要。但是,证据来源通常很大且具有异质性,因此,只有通过系统和全面的证据综合,才能了解哪些干预措施有效、针对谁有效以及在什么情况下有效。许多障碍阻碍了全面的证据综合,导致干预效果的普遍性存在不确定性,包括不准确的标题/摘要/关键词术语(阻碍文献检索工作)、研究方法的报告不明确(导致对研究严谨性的评估不准确)以及报告的参与者特征、结果和关键变量较差(阻碍总体效果的计算或影响修饰符的检查)。为了解决这些问题,并通过将初级研究纳入证据综合来扩大其影响范围,我们提供了一套实用的指南,以帮助预防科学家准备好进行综合研究。我们使用最近的正念试验作为实证示例来展开讨论,并展示了确保以下几点的方法:(1)初级研究是可发现的;(2)综合所需的数据类型是存在的;(3)这些数据是易于综合的。我们强调了几个可以帮助作者完成这些工作的工具和实践,例如使用数据驱动的方法来制定标题、摘要和关键词,或者为每个项目创建一个存储库来托管所有与研究相关的数据文件。我们还为标准化数据设计和公共存档提供了分步指导和软件建议,以促进可综合研究。