期刊
JOURNAL OF CLINICAL EPIDEMIOLOGY
卷 136, 期 -, 页码 189-202出版社
ELSEVIER SCIENCE INC
DOI: 10.1016/j.jclinepi.2021.05.012
关键词
Data integrity; Research misconduct; Scientific misconduct; Randomization; Methods; Scoping review
资金
- Elsevier
This study provides an overview of methods to investigate research misconduct in health-related research. While measures against textual plagiarism are well implemented, tools for other forms of research misconduct are lacking standardization and formal validation, calling for further development of automatic tools and routine validation of these methods.
Objective: To give an overview of the available methods to investigate research misconduct in health-related research. Study Design and Setting: In this scoping review, we conducted a literature search in MEDLINE, Embase, The Cochrane CENTRAL Register of Studies Online (CRSO), and The Virtual Health Library portal up to July 2020. We included papers that mentioned and/or described methods for screening or assessing research misconduct in health-related research. We categorized identified methods into the following four groups according to their scopes: overall concern, textual concern, image concern, and data concern. Results: We included 57 papers reporting on 27 methods: two on overall concern, four on textual concern, three on image concern, and 18 on data concern. Apart from the methods to locate textual plagiarism and image manipulation, all other methods, be it theoretical or empirical, are based on examples, are not standardized, and lack formal validation. Conclusion: Existing methods cover a wide range of issues regarding research misconduct. Although measures to counteract textual plagiarism are well implemented, tools to investigate other forms of research misconduct are rudimentary and labour-intensive. To cope with the rising challenge of research misconduct, further development of automatic tools and routine validation of these methods is needed. Trial registration number: Center for Open Science (OSF) ( https:// osf.io/ mq89w). (c) 2021 Elsevier Inc. All rights reserved.
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