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Prevalence of questionable research practices, research misconduct and their potential explanatory factors: A survey among academic researchers in The Netherlands

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  • Gowri Gopalakrishna
  • Gerben ter Riet
  • Gerko Vink
  • Ineke Stoop
  • Jelte M Wicherts
  • Lex M Bouter

Abstract

Prevalence of research misconduct, questionable research practices (QRPs) and their associations with a range of explanatory factors has not been studied sufficiently among academic researchers. The National Survey on Research Integrity targeted all disciplinary fields and academic ranks in the Netherlands. It included questions about engagement in fabrication, falsification and 11 QRPs over the previous three years, and 12 explanatory factor scales. We ensured strict identity protection and used the randomized response method for questions on research misconduct. 6,813 respondents completed the survey. Prevalence of fabrication was 4.3% (95% CI: 2.9, 5.7) and of falsification 4.2% (95% CI: 2.8, 5.6). Prevalence of QRPs ranged from 0.6% (95% CI: 0.5, 0.9) to 17.5% (95% CI: 16.4, 18.7) with 51.3% (95% CI: 50.1, 52.5) of respondents engaging frequently in at least one QRP. Being a PhD candidate or junior researcher increased the odds of frequently engaging in at least one QRP, as did being male. Scientific norm subscription (odds ratio (OR) 0.79; 95% CI: 0.63, 1.00) and perceived likelihood of detection by reviewers (OR 0.62, 95% CI: 0.44, 0.88) were associated with engaging in less research misconduct. Publication pressure was associated with more often engaging in one or more QRPs frequently (OR 1.22, 95% CI: 1.14, 1.30). We found higher prevalence of misconduct than earlier surveys. Our results suggest that greater emphasis on scientific norm subscription, strengthening reviewers in their role as gatekeepers of research quality and curbing the “publish or perish” incentive system promotes research integrity.

Suggested Citation

  • Gowri Gopalakrishna & Gerben ter Riet & Gerko Vink & Ineke Stoop & Jelte M Wicherts & Lex M Bouter, 2022. "Prevalence of questionable research practices, research misconduct and their potential explanatory factors: A survey among academic researchers in The Netherlands," PLOS ONE, Public Library of Science, vol. 17(2), pages 1-16, February.
    • Handle: RePEc:plo:pone00:0263023
    DOI: 10.1371/journal.pone.0263023
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    References listed on IDEAS

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    1. Melissa S. Anderson & Emily A. Ronning & Raymond De Vries & Brian C. Martinson, 2010. "Extending the Mertonian Norms: Scientists' Subscription to Norms of Research," The Journal of Higher Education, Taylor & Francis Journals, vol. 81(3), pages 366-393, May.
    2. van Buuren, Stef & Groothuis-Oudshoorn, Karin, 2011. "mice: Multivariate Imputation by Chained Equations in R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 45(i03).
    3. Jelte M. Wicherts, 2011. "Psychology must learn a lesson from fraud case," Nature, Nature, vol. 480(7375), pages 7-7, December.
    4. List, John A, et al, 2001. "Academic Economists Behaving Badly? A Survey on Three Areas of Unethical Behavior," Economic Inquiry, Western Economic Association International, vol. 39(1), pages 162-170, January.
    5. David Moher & Lex Bouter & Sabine Kleinert & Paul Glasziou & Mai Har Sham & Virginia Barbour & Anne-Marie Coriat & Nicole Foeger & Ulrich Dirnagl, 2020. "The Hong Kong Principles for assessing researchers: Fostering research integrity," PLOS Biology, Public Library of Science, vol. 18(7), pages 1-14, July.
    6. Charness, Gary & Gneezy, Uri, 2012. "Strong Evidence for Gender Differences in Risk Taking," Journal of Economic Behavior & Organization, Elsevier, vol. 83(1), pages 50-58.
    7. Rubin, Donald B, 1986. "Statistical Matching Using File Concatenation with Adjusted Weights and Multiple Imputations," Journal of Business & Economic Statistics, American Statistical Association, vol. 4(1), pages 87-94, January.
    8. Little, Roderick J A, 1988. "Missing-Data Adjustments in Large Surveys," Journal of Business & Economic Statistics, American Statistical Association, vol. 6(3), pages 287-296, July.
    9. Daniele Fanelli, 2009. "How Many Scientists Fabricate and Falsify Research? A Systematic Review and Meta-Analysis of Survey Data," PLOS ONE, Public Library of Science, vol. 4(5), pages 1-11, May.
    10. Niels Mejlgaard & Lex M. Bouter & George Gaskell & Panagiotis Kavouras & Nick Allum & Anna-Kathrine Bendtsen & Costas A. Charitidis & Nik Claesen & Kris Dierickx & Anna Domaradzka & Andrea Reyes Elizo, 2020. "Research integrity: nine ways to move from talk to walk," Nature, Nature, vol. 586(7829), pages 358-360, October.
    11. Maarten J. L. F. Cruyff & Ardo Van Den Hout & Peter G. M. Van Der Heijden, 2008. "The analysis of randomized response sum score variables," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 70(1), pages 21-30, February.
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    1. Freuli, Francesca & Held, Leonhard & Heyard, Rachel, 2022. "Replication success under questionable research practices – a simulation study," MetaArXiv s4b65, Center for Open Science.
    2. María Núñez-Núñez & Naomi Cano-Ibáñez & Javier Zamora & Aurora Bueno-Cavanillas & Khalid Saeed Khan, 2023. "Assessing the Integrity of Clinical Trials Included in Evidence Syntheses," IJERPH, MDPI, vol. 20(12), pages 1-13, June.
    3. Sarstedt, Marko & Adler, Susanne J., 2023. "An advanced method to streamline p-hacking," Journal of Business Research, Elsevier, vol. 163(C).

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