Comparar métodos
Examine os métodos selecionados lado a lado; as linhas que diferem ficam destacadas.
| Fabricação e Falsificação de Dados× | Conflito de Interesses em Pesquisa× | |
|---|---|---|
| Área | Ética em pesquisa | Ética em pesquisa |
| Família | Process / pipeline | Process / pipeline |
| Ano de origem≠ | 2005 | 2013 |
| Autor original≠ | U.S. Office of Research Integrity; definitions in federal policy 42 CFR 93 | Multiple (NIH, ICMJE, institutional COI policies) |
| Tipo≠ | Standard | Guideline |
| Fonte seminal≠ | U.S. Office of Research Integrity. (2005). Public Health Service Policy on Research Misconduct. 42 CFR Part 93. Definitions of fabrication and falsification. link ↗ | International Committee of Medical Journal Editors. (2023). Defining the Role of Authors and Contributors. ICMJE Recommendations for Manuscript Authorship. link ↗ |
| Outros nomes | FFP Data Violations, Data Integrity Violations | COI, Conflicts of Interest |
| Relacionados | 3 | 3 |
| Resumo≠ | 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. |
| ScholarGateConjunto de dados ↗ |
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