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独立讨论部分可提高已发表研究的推理可重复性。

Independent discussion sections for improving inferential reproducibility in published research.

机构信息

Department of Anesthesiology, Washington University School of Medicine, St Louis, MO, USA.

Departments of Health Research and Policy, Medicine, Biomedical Data Science, and Statistics, Meta-Research Innovation Center, Stanford University, Palo Alto, CA, USA.

出版信息

Br J Anaesth. 2019 Apr;122(4):413-420. doi: 10.1016/j.bja.2018.12.010. Epub 2019 Jan 22.

Abstract

There is a reproducibility crisis in science. There are many potential contributors to replication failure in research across the translational continuum. In this perspective piece, we focus on the narrow topic of inferential reproducibility. Although replication of methods and results is necessary to demonstrate reproducibility, it is not sufficient. Also fundamental is consistent interpretation in the Discussion section. Current deficiencies in the Discussion sections of manuscripts might limit the inferential reproducibility of scientific research. Lack of contextualisation using systematic reviews, overinterpretation and misinterpretation of results, and insufficient acknowledgement of limitations are common problems in Discussion sections; these deficiencies can harm the translational process. Proposed solutions include eliminating or not reading Discussions, writing accompanying editorials, and post-publication review and comments; however, none of these solutions works very well. A second Discussion written by an independent author with appropriate expertise in research methodology is a new testable solution that could help probe inferential reproducibility, and address some deficiencies in primary Discussion sections.

摘要

科学领域存在可重复性危机。在整个转化连续体的研究中,有许多潜在因素会导致研究无法重复。在这篇观点文章中,我们专注于推理可重复性这一狭隘的主题。虽然复制方法和结果对于证明可重复性是必要的,但这还不够。在讨论部分的一致解释也同样重要。目前,手稿讨论部分的缺陷可能会限制科学研究的推理可重复性。使用系统评价缺乏语境化、对结果的过度解释和错误解释,以及对局限性的充分承认都是讨论部分常见的问题;这些缺陷会损害转化过程。提出的解决方案包括删除或不阅读讨论部分、撰写相关社论,以及发表后审查和评论;然而,这些解决方案都没有很好地发挥作用。由具有适当研究方法专业知识的独立作者撰写的第二个讨论是一个新的可测试解决方案,可以帮助探究推理可重复性,并解决主要讨论部分的一些缺陷。

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