评估一个作者或作者集团收集工作的科学完整性
Jeremy Nielsen1, Esmée M Bordewijk2, Lyle C Gurrin3
1Department of Obstetrics and Gynaecology, Monash University, Clayton, Australia.
Journal of clinical epidemiology
|January 12, 2025
概括
这项研究引入了一种用于评估科学出版物研究完整性的新方法. 它将随机试验的统计分析与个人论文评论相结合,以检测作者或团体的学术不当行为.
科学领域:
- 医学研究诚信 医学研究诚信
- 图书统计学 图书统计学
- 科学出版伦理学 出版伦理学
背景情况:
- 人们越来越担心临床研究中的欺诈或伪造数据.
- 单个作者或群体发表多篇论文的普遍性,这些论文表现出数据完整性问题.
- 缺乏综合统计和个人论文评估的综合方法,用于研究完整性审查.
研究的目的:
- 提出一个系统的方法来调查数据完整性通过一个作者或作者组的论文集合.
- 为了研究完整性评估,将既定的统计技术与实际可行性评估相结合.
- 提高期刊和出版商识别潜在不值得信赖的研究的能力.
主要方法:
- 系统的文献搜索 (PubMed,谷歌学者,Retraction Watch) 和试验注册表的搜索.
- 研究信息的表格化,以评估注册,执行和出版之间的一致性.
- 对于不可行研究特征 (治理,方法,结果,报告) 的个人论文评估.
- 数据重复表的对比比较和基线特征的评估.
- 应用统计方法 (如卡莱尔方法,本福德定律) 来评估随机化和数据模式.
主要成果:
- 提出的方法为研究完整性评估提供了一种系统和可重复的方法.
- 识别潜在的数据重复,不可行的研究特征和报告数据中的不一致性.
- 提供了一个框架,用于检测表明学术不当行为的模式.
- 强调在出现严重问题时,需要由期刊,出版商和机构进行彻底调查.
结论:
- 开发的方法有效地结合了统计分析和务实评估来评估研究完整性.
- 赋予期刊和出版商的工具,以更好地识别潜在的欺诈性研究的集合.
- 有助于保持科学文献的可信性和可靠性.
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