Comparer des méthodes

	Data Fabrication and Falsification	Conflict of Interest in Research
Domaine	Éthique de la recherche	Éthique de la recherche
Famille	Process / pipeline	Process / pipeline
Année d'origine	2005	2013
Auteur d'origine	U.S. Office of Research Integrity; definitions in federal policy 42 CFR 93	Multiple (NIH, ICMJE, institutional COI policies)
Type	Standard	Guideline
Source fondatrice	U.S. Office of Research Integrity. (2005). Public Health Service Policy on Research Misconduct. 42 CFR Part 93. Definitions of fabrication and falsification.	International Committee of Medical Journal Editors. (2023). Defining the Role of Authors and Contributors. ICMJE Recommendations for Manuscript Authorship.
Alias	FFP Data Violations, Data Integrity Violations	COI, Conflicts of Interest
Apparentées	3	3
Résumé	Data fabrication and falsification are serious forms of research misconduct involving intentional misrepresentation of research data. Fabrication means inventing data that were never actually collected; falsification means altering authentic data to change the meaning. Both undermine scientific integrity, waste research resources, and can harm research subjects and the public. Federal policy (42 CFR Part 93) formally defines these violations; detection is improving through statistical analysis tools and data transparency practices; prevention requires robust data governance and culture of accountability.	A conflict of interest (COI) in research exists when a researcher has financial, professional, or personal interests that might bias their research judgment or outcomes. Conflicts are inherent in research communities—researchers often have legitimate stakes in their research's success—but unmanaged conflicts compromise research integrity and public trust. Managing COI requires transparent disclosure, institutional oversight, and proactive mitigation strategies to minimize bias risk while allowing legitimate research to proceed.