Skip to main content
bioRxiv
  • Home
  • About
  • Submit
  • ALERTS / RSS
Advanced Search
New Results

Why do scientists fabricate and falsify data? A matched-control analysis of papers containing problematic image duplications

View ORCID ProfileDaniele Fanelli, Rodrigo Costas, Ferric C. Fang, Arturo Casadevall, Elisabeth M. Bik
doi: https://doi.org/10.1101/126805
Daniele Fanelli
1Meta-Research Innovation Center at Stanford (METRICS), 1070 Arastradero Road, Stanford University, Palo Alto, CA 94304, USA.
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Daniele Fanelli
  • For correspondence: email@danielefanelli.com
Rodrigo Costas
2Centre for Science and Technology Studies (CWTS), Leiden University, P.O. Box 905 2300 AX Leiden, The Netherlands.
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Ferric C. Fang
3Departments of Laboratory Medicine and Microbiology, University of Washington School of Medicine, Seattle, WA 98195.
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Arturo Casadevall
4Department of Molecular Microbiology and Immunology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205.
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Elisabeth M. Bik
5uBiome, San Francisco, CA 94105
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • Abstract
  • Full Text
  • Info/History
  • Metrics
  • Supplementary material
  • Preview PDF
Loading

ABSTRACT

It is commonly hypothesized that scientists are more likely to engage in data falsification and fabrication when they are subject to pressures to publish, when they are not restrained by forms of social control, when they work in countries lacking policies to tackle scientific misconduct, and when they are male. Evidence to test these hypotheses, however, is inconclusive due to the difficulties of obtaining unbiased data.

Here we report a pre-registered test of these four hypotheses, conducted on papers that were identified in a previous study as containing problematic image duplications through a systematic screening of the journal PLoS ONE. Image duplications were classified into three categories based on their complexity, with category 1 being most likely to reflect unintentional error and category 3 being most likely to reflect intentional fabrication. Multiple parameters connected to the hypotheses above were tested with a matched-control paradigm, by collecting two controls for each paper containing duplications.

Category 1 duplications were mostly not associated with any of the parameters tested, in accordance with the assumption that these duplications were mostly not due to misconduct. Category 2 and 3, however, exhibited numerous statistically significant associations. Results of univariable and multivariable analyses support the hypotheses that academic culture, peer control, cash-based publication incentives and national misconduct policies might affect scientific integrity. Significant correlations between the risk of image duplication and individual publication rates or gender, however, were only observed in secondary and exploratory analyses.

Country-level parameters generally exhibited effects of larger magnitude than individual-level parameters, because a subset of countries was significantly more likely to produce problematic image duplications. Promoting good research practices in all countries should be a priority for the international research integrity agenda.

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.
Back to top
PreviousNext
Posted April 12, 2017.
Download PDF

Supplementary Material

Email

Thank you for your interest in spreading the word about bioRxiv.

NOTE: Your email address is requested solely to identify you as the sender of this article.

Enter multiple addresses on separate lines or separate them with commas.
Why do scientists fabricate and falsify data? A matched-control analysis of papers containing problematic image duplications
(Your Name) has forwarded a page to you from bioRxiv
(Your Name) thought you would like to see this page from the bioRxiv website.
CAPTCHA
This question is for testing whether or not you are a human visitor and to prevent automated spam submissions.
Share
Why do scientists fabricate and falsify data? A matched-control analysis of papers containing problematic image duplications
Daniele Fanelli, Rodrigo Costas, Ferric C. Fang, Arturo Casadevall, Elisabeth M. Bik
bioRxiv 126805; doi: https://doi.org/10.1101/126805
Digg logo Reddit logo Twitter logo Facebook logo Google logo LinkedIn logo Mendeley logo
Citation Tools
Why do scientists fabricate and falsify data? A matched-control analysis of papers containing problematic image duplications
Daniele Fanelli, Rodrigo Costas, Ferric C. Fang, Arturo Casadevall, Elisabeth M. Bik
bioRxiv 126805; doi: https://doi.org/10.1101/126805

Citation Manager Formats

  • BibTeX
  • Bookends
  • EasyBib
  • EndNote (tagged)
  • EndNote 8 (xml)
  • Medlars
  • Mendeley
  • Papers
  • RefWorks Tagged
  • Ref Manager
  • RIS
  • Zotero
  • Tweet Widget
  • Facebook Like
  • Google Plus One

Subject Area

  • Scientific Communication and Education
Subject Areas
All Articles
  • Animal Behavior and Cognition (3607)
  • Biochemistry (7581)
  • Bioengineering (5529)
  • Bioinformatics (20809)
  • Biophysics (10338)
  • Cancer Biology (7988)
  • Cell Biology (11647)
  • Clinical Trials (138)
  • Developmental Biology (6611)
  • Ecology (10217)
  • Epidemiology (2065)
  • Evolutionary Biology (13630)
  • Genetics (9550)
  • Genomics (12854)
  • Immunology (7925)
  • Microbiology (19555)
  • Molecular Biology (7668)
  • Neuroscience (42147)
  • Paleontology (308)
  • Pathology (1258)
  • Pharmacology and Toxicology (2203)
  • Physiology (3269)
  • Plant Biology (7051)
  • Scientific Communication and Education (1294)
  • Synthetic Biology (1952)
  • Systems Biology (5429)
  • Zoology (1119)