Influential methods reports for group-randomized trials and related designs.
Influential methods reports for group-randomized trials and related designs.
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有影响力的方法报告针对群体随机试验和相关设计。
DOI：
10.1177/17407745211063423
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发表时间：
2022-08
期刊：
影响因子：
2.7
通讯作者：
Murray, David M.
中科院分区：
文献类型：
--
作者：
Murray, David M.
关键词：
本文确定了到2020年发表的组随机试验和相关设计的最有影响力的方法报告。许多干预措施被提供给真实的或虚拟的群体中的参与者，或者由共享的干预者定义的群体中的参与者，使得期望在对同一群体中的参与者进行的观察之间存在正相关。这些干预措施通常使用组或群随机试验、个体随机分组治疗试验或阶梯楔形组或群随机试验进行评估。这些试验面临的方法学问题超出了更熟悉的个体随机对照试验中遇到的问题。检索PubMed以识别候选方法报告;检索由作者已知的报告补充。作者审查了候选报告，仅包括关注感兴趣设计的报告。引用计数和相对引用率，一个新的文献计量学工具，在美国国立卫生研究院开发的，被用来确定有影响力的报告。相对引用率通过比较参考文献的引用率与其他引用参考文献的文章的引用率来衡量文章水平的影响力。截至2020年，共确定了1043份报告。根据相对引用率或引用计数，使用三种设计中每种设计的特定标准，55份被认为是最有影响力的，其中32份为组随机试验报告，7份为单独随机组治疗试验报告，16份为阶梯楔形组随机试验报告。许多有影响力的报告是早期的出版物，这些出版物引起了人们对这些设计与更熟悉的个体随机对照试验的区别的注意。另一些是教科书，涵盖了这些设计的广泛问题。其他报告是关于适用于特定类型数据的分析方法的“第一次报告”（例如，二进制数据、序数数据），对于这些研究中通常遇到的特征（例如，不相等的群集大小、损耗），或研究设计中的重要变化（例如，重复测量，队列与横截面）。许多人提出了计算样本量的方法。其他人描述了这些设计如何应用于一个新的领域（例如，传播和实施研究）。相对引用率最高的报告是CONSORT对每种设计的陈述。总的来说，这些有影响力的报告涉及了研究人员非常感兴趣的主题，他们可能会考虑使用这些设计之一，并需要指导他们选择最合适的研究问题设计以及设计，分析和样本量的最佳方法。
This paper identifies the most influential methods reports for group-randomized trials and related designs published through 2020. Many interventions are delivered to participants in real or virtual groups or in groups defined by a shared interventionist so that there is an expectation for positive correlation among observations taken on participants in the same group. These interventions are typically evaluated using a group- or cluster-randomized trial, an individually-randomized group treatment trial, or a stepped wedge group- or cluster-randomized trial. These trials face methodological issues beyond those encountered in the more familiar individually-randomized controlled trial. PubMed was searched to identify candidate methods reports; that search was supplemented by reports known to the author. Candidate reports were reviewed by the author to include only those focused on the designs of interest. Citation counts and the relative citation ratio, a new bibliometric tool developed at the National Institutes of Health, were used to identify influential reports. The relative citation ratio measures influence at the article level by comparing the citation rate of the reference article to the citation rates of the articles cited by other articles that also cite the reference article. 1043 reports were identified that were published through 2020. Fifty-five were deemed to be most influential based on their relative citation ratio or their citation count using criteria specific to each of the three designs, with 32 group-randomized trial reports, 7 individually-randomized group treatment trial reports, and 16 stepped wedge group-randomized trial reports. Many of the influential reports were early publications that drew attention to the issues that distinguish these designs from the more familiar individually-randomized controlled trial. Others were textbooks that covered a wide range of issues for these designs. Others were “first reports” on analytic methods appropriate for a specific type of data (e.g., binary data, ordinal data), for features commonly encountered in these studies (e.g., unequal cluster size, attrition), or for important variations in study design (e.g., repeated measures, cohort vs cross-section). Many presented methods for sample size calculations. Others described how these designs could be applied to a new area (e.g., dissemination and implementation research). Among the reports with the highest relative citation ratios were the CONSORT statements for each design. Collectively, the influential reports address topics of great interest to investigators who might consider using one of these designs and need guidance on selecting the most appropriate design for their research question and on the best methods for design, analysis, and sample size.
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影响因子：
2
作者：
Andridge, Rebecca R.;Shoben, Abigail B.;Muller, Keith E.;Murray, David M.
通讯作者：
Murray, David M.
报告在群集随机试验中不遵守：系统评价。
DOI：
10.1177/1740774518761666
发表时间：
2018-06
期刊：
Clinical trials (London, England)
影响因子：
--
作者：
Agbla SC;DiazOrdaz K
通讯作者：
DiazOrdaz K
影响因子：
7.2
作者：
Adams, G;Gulliford, MC;Campbell, MJ
通讯作者：
Campbell, MJ
影响因子：
105.7
作者：
Campbell, MK;Elbourne, DR;Altman, DG
通讯作者：
Altman, DG
影响因子：
7
作者：
Bauer, Daniel J.;Gottfredson, Nisha C.;Zucker, Robert A.
通讯作者：
Zucker, Robert A.