IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0188247.html
   My bibliography  Save this article

Determinants of selective reporting: A taxonomy based on content analysis of a random selection of the literature

Author

Listed:
  • Jenny T van der Steen
  • Cornelis A van den Bogert
  • Mirjam C van Soest-Poortvliet
  • Soulmaz Fazeli Farsani
  • René H J Otten
  • Gerben ter Riet
  • Lex M Bouter

Abstract

Background: Selective reporting is wasteful, leads to bias in the published record and harms the credibility of science. Studies on potential determinants of selective reporting currently lack a shared taxonomy and a causal framework. Objective: To develop a taxonomy of determinants of selective reporting in science. Design: Inductive qualitative content analysis of a random selection of the pertinent literature including empirical research and theoretical reflections. Methods: Using search terms for bias and selection combined with terms for reporting and publication, we systematically searched the PubMed, Embase, PsycINFO and Web of Science databases up to January 8, 2015. Of the 918 articles identified, we screened a 25 percent random selection. From eligible articles, we extracted phrases that mentioned putative or possible determinants of selective reporting, which we used to create meaningful categories. We stopped when no new categories emerged in the most recently analyzed articles (saturation). Results: Saturation was reached after analyzing 64 articles. We identified 497 putative determinants, of which 145 (29%) were supported by empirical findings. The determinants represented 12 categories (leaving 3% unspecified): focus on preferred findings (36%), poor or overly flexible research design (22%), high-risk area and its development (8%), dependence upon sponsors (8%), prejudice (7%), lack of resources including time (3%), doubts about reporting being worth the effort (3%), limitations in reporting and editorial practices (3%), academic publication system hurdles (3%), unfavorable geographical and regulatory environment (2%), relationship and collaboration issues (2%), and potential harm (0.4%). Conclusions: We designed a taxonomy of putative determinants of selective reporting consisting of 12 categories. The taxonomy may help develop theory about causes of selection bias and guide policies to prevent selective reporting.

Suggested Citation

  • Jenny T van der Steen & Cornelis A van den Bogert & Mirjam C van Soest-Poortvliet & Soulmaz Fazeli Farsani & René H J Otten & Gerben ter Riet & Lex M Bouter, 2018. "Determinants of selective reporting: A taxonomy based on content analysis of a random selection of the literature," PLOS ONE, Public Library of Science, vol. 13(2), pages 1-15, February.
    • Handle: RePEc:plo:pone00:0188247
    DOI: 10.1371/journal.pone.0188247
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0188247
    Download Restriction: no
    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0188247&type=printable
    Download Restriction: no
    File URL: https://libkey.io/10.1371/journal.pone.0188247?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. John P A Ioannidis, 2005. "Why Most Published Research Findings Are False," PLOS Medicine, Public Library of Science, vol. 2(8), pages 1-1, August.
    2. Mojtaba Vaismoradi & Hannele Turunen & Terese Bondas, 2013. "Content analysis and thematic analysis: Implications for conducting a qualitative descriptive study," Nursing & Health Sciences, John Wiley & Sons, vol. 15(3), pages 398-405, September.
    3. David Moher & Alessandro Liberati & Jennifer Tetzlaff & Douglas G Altman & The PRISMA Group, 2009. "Preferred Reporting Items for Systematic Reviews and Meta-Analyses: The PRISMA Statement," PLOS Medicine, Public Library of Science, vol. 6(7), pages 1-6, July.
    4. Emily S Sena & H Bart van der Worp & Philip M W Bath & David W Howells & Malcolm R Macleod, 2010. "Publication Bias in Reports of Animal Stroke Studies Leads to Major Overstatement of Efficacy," PLOS Biology, Public Library of Science, vol. 8(3), pages 1-8, March.
    5. Daniele Fanelli, 2010. "Do Pressures to Publish Increase Scientists' Bias? An Empirical Support from US States Data," PLOS ONE, Public Library of Science, vol. 5(4), pages 1-7, April.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Marjan Bakker & Coosje L S Veldkamp & Marcel A L M van Assen & Elise A V Crompvoets & How Hwee Ong & Brian A Nosek & Courtney K Soderberg & David Mellor & Jelte M Wicherts, 2020. "Ensuring the quality and specificity of preregistrations," PLOS Biology, Public Library of Science, vol. 18(12), pages 1-18, December.
    2. Horbach, Serge & Aagaard, Kaare & Schneider, Jesper W., 2021. "Meta-Research: How problematic citing practices distort science," MetaArXiv aqyhg, Center for Open Science.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Matteo M. Galizzi & Daniel Navarro-Martinez, 2019. "On the External Validity of Social Preference Games: A Systematic Lab-Field Study," Management Science, INFORMS, vol. 65(3), pages 976-1002, March.
    2. Li Liu & Qinji Su & Lixia Li & Xiaohui Lin & Yu Gan & Sidong Chen, 2014. "The Common Variant rs4444235 near BMP4 Confers Genetic Susceptibility of Colorectal Cancer: An Updated Meta-Analysis Based on a Comprehensive Statistical Strategy," PLOS ONE, Public Library of Science, vol. 9(6), pages 1-8, June.
    3. Marlo M Vernon & E Andrew Balas & Shaher Momani, 2018. "Are university rankings useful to improve research? A systematic review," PLOS ONE, Public Library of Science, vol. 13(3), pages 1-15, March.
    4. Constance Holman & Sophie K Piper & Ulrike Grittner & Andreas Antonios Diamantaras & Jonathan Kimmelman & Bob Siegerink & Ulrich Dirnagl, 2016. "Where Have All the Rodents Gone? The Effects of Attrition in Experimental Research on Cancer and Stroke," PLOS Biology, Public Library of Science, vol. 14(1), pages 1-12, January.
    5. Bernhard Voelkl & Lucile Vogt & Emily S Sena & Hanno Würbel, 2018. "Reproducibility of preclinical animal research improves with heterogeneity of study samples," PLOS Biology, Public Library of Science, vol. 16(2), pages 1-13, February.
    6. Émilie Hudon & Catherine Hudon & Mireille Lambert & Mathieu Bisson & Maud-Christine Chouinard, 2021. "Generic Self-Reported Questionnaires Measuring Self-Management: A Scoping Review," Clinical Nursing Research, , vol. 30(6), pages 855-865, July.
    7. Fabo, Brian & Jančoková, Martina & Kempf, Elisabeth & Pástor, Ľuboš, 2021. "Fifty shades of QE: Comparing findings of central bankers and academics," Journal of Monetary Economics, Elsevier, vol. 120(C), pages 1-20.
    8. David Pontille & Didier Torny, 2013. "Behind the scenes of scientific articles: defining categories of fraud and regulating cases," CSI Working Papers Series 031, Centre de Sociologie de l'Innovation (CSI), Mines ParisTech.
    9. Pascucci, Domenico & Sassano, Michele & Nurchis, Mario Cesare & Cicconi, Michela & Acampora, Anna & Park, Daejun & Morano, Carmen & Damiani, Gianfranco, 2021. "Impact of interprofessional collaboration on chronic disease management: Findings from a systematic review of clinical trial and meta-analysis," Health Policy, Elsevier, vol. 125(2), pages 191-202.
    10. Zacharias Maniadis & Fabio Tufano & John A. List, 2014. "One Swallow Doesn't Make a Summer: Reply to Kataria," Econ Journal Watch, Econ Journal Watch, vol. 11(1), pages 11-16, January.
    11. Mark D Lindner & Richard K Nakamura, 2015. "Examining the Predictive Validity of NIH Peer Review Scores," PLOS ONE, Public Library of Science, vol. 10(6), pages 1-12, June.
    12. Waller, Daniel & Brooks, Fiona & Perry, Lin & Kang, Melissa & Steinbeck, Katharine, 2021. "Australian federal, state and territory policy on the health and wellbeing of young people: A scoping review," Health Policy, Elsevier, vol. 125(8), pages 1065-1076.
    13. Carole J. Lee & Cassidy R. Sugimoto & Guo Zhang & Blaise Cronin, 2013. "Bias in peer review," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 64(1), pages 2-17, January.
    14. Vasja Roblek & Oshane Thorpe & Mirjana Pejic Bach & Andrej Jerman & Maja Meško, 2020. "The Fourth Industrial Revolution and the Sustainability Practices: A Comparative Automated Content Analysis Approach of Theory and Practice," Sustainability, MDPI, vol. 12(20), pages 1-27, October.
    15. Chin, Jason & Zeiler, Kathryn, 2021. "Replicability in Empirical Legal Research," LawArXiv 2b5k4, Center for Open Science.
    16. Salandra, Rossella, 2018. "Knowledge dissemination in clinical trials: Exploring influences of institutional support and type of innovation on selective reporting," Research Policy, Elsevier, vol. 47(7), pages 1215-1228.
    17. Tugce Yildizoglu & Jan-Marek Weislogel & Farhan Mohammad & Edwin S-Y Chan & Pryseley N Assam & Adam Claridge-Chang, 2015. "Estimating Information Processing in a Memory System: The Utility of Meta-analytic Methods for Genetics," PLOS Genetics, Public Library of Science, vol. 11(12), pages 1-27, December.
    18. Phadiel Hoosen & Sabirah Adams & Habib Tiliouine & Shazly Savahl, 2022. "Youth and Adolescents’ Perceptions of Violence in Post-Apartheid South Africa: A Systematic Review of the Literature," Child Indicators Research, Springer;The International Society of Child Indicators (ISCI), vol. 15(3), pages 885-911, June.
    19. Ute Laermann-Nguyen & Martin Backfisch, 2021. "Innovation crisis in the pharmaceutical industry? A survey," SN Business & Economics, Springer, vol. 1(12), pages 1-37, December.
    20. Hadi Alizadeh & Ayyoob Sharifi & Safiyeh Damanbagh & Hadi Nazarnia & Mohammad Nazarnia, 2023. "Impacts of the COVID-19 pandemic on the social sphere and lessons for crisis management: a literature review," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 117(3), pages 2139-2164, July.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:plo:pone00:0188247. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: plosone (email available below). General contact details of provider: https://journals.plos.org/plosone/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.