A survey of experts to identify methods to detect problematic studies: Stage 1 of the INSPECT-SR Project

Jack D Wilkinson, Calvin Heal, Georgios A Antoniou, Ella Flemyng, Alison Avenell, Virgina Barbour, Esmee M Bordewijk, Nicholas JL Brown, Mike Clarke, Jo Dumville, Lyle C Gurrin, Jill A Hayden, Kylie E Hunter, Emily Lam, Toby Lasserson, Tianjing Li, Sarah Lensen, Jianping Liu, Andreas Lundh, Gideon Meyerowitz-Katz, Ben W Mol, Neil E O'Connell, Lisa Parker, Barbara Redman, Anna Lene Seidler, kyle Sheldrick, Emma Sydenham, Madelon van Wely, Lisa Bero, Jamie J Kirkham
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Abstract

Background Randomised controlled trials (RCTs) inform healthcare decisions. Unfortunately, some published RCTs contain false data, and some appear to have been entirely fabricated. Systematic reviews are performed to identify and synthesise all RCTs which have been conducted on a given topic. This means that any of these 'problematic studies' are likely to be included, but there are no agreed methods for identifying them. The INSPECT-SR project is developing a tool to identify problematic RCTs in systematic reviews of healthcare-related interventions. The tool will guide the user through a series of `checks' to determine a study's authenticity. The first objective in the development process is to assemble a comprehensive list of checks to consider for inclusion. Methods We assembled an initial list of checks for assessing the authenticity of research studies, with no restriction to RCTs, and categorised these into five domains: Inspecting results in the paper; Inspecting the research team; Inspecting conduct, governance, and transparency; Inspecting text and publication details; Inspecting the individual participant data. We implemented this list as an online survey, and invited people with expertise and experience of assessing potentially problematic studies to participate through professional networks and online forums. Participants were invited to provide feedback on the checks on the list, and were asked to describe any additional checks they knew of, which were not featured in the list. Results Extensive feedback on an initial list of 102 checks was provided by 71 participants based in 16 countries across five continents. Fourteen new checks were proposed across the five domains, and suggestions were made to reword checks on the initial list. An updated list of checks was constructed, comprising 116 checks. Many participants expressed a lack of familiarity with statistical checks, and emphasized the importance of feasibility of the tool. Conclusions A comprehensive list of trustworthiness checks has been produced. The checks will be evaluated to determine which should be included in the INSPECT-SR tool.
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专家调查,确定发现问题研究的方法:INSPECT-SR 项目第 1 阶段
背景 随机对照试验(RCT)为医疗决策提供依据。遗憾的是,一些已发表的 RCT 包含虚假数据,有些似乎完全是捏造的。系统综述的目的是识别和综合针对特定主题进行的所有 RCT。这意味着任何这些 "有问题的研究 "都有可能被包括在内,但目前还没有公认的方法来识别它们。INSPECT-SR 项目正在开发一种工具,用于识别医疗保健相关干预措施系统综述中存在问题的 RCT。该工具将引导用户通过一系列 "检查 "来确定研究的真实性。开发过程中的第一个目标是收集一份全面的检查清单,以考虑是否纳入。方法 我们收集了一份用于评估研究真实性的初步检查清单,不局限于 RCT,并将其分为五个领域:检查论文结果;检查研究团队;检查行为、管理和透明度;检查文本和出版细节;检查参与者个人数据。我们以在线调查的形式实施了这份清单,并通过专业网络和在线论坛邀请在评估潜在问题研究方面拥有专业知识和经验的人员参与其中。我们邀请参与者就清单中的检查内容提供反馈意见,并要求他们描述他们所知道的、清单中没有列出的其他检查内容。结果 来自五大洲 16 个国家的 71 名参与者就 102 项检查的初步清单提供了广泛的反馈意见。在五个领域中提出了 14 项新的检查,并对初始清单中的检查提出了重新措辞的建议。更新后的检查清单由 116 项检查组成。许多与会者表示不熟悉统计核对,并强调了工具可行性的重要性。结论 已编制出一份全面的可信度检查清单。将对这些检查进行评估,以确定哪些检查应纳入 INSPECT-SR 工具。
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