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A Systems Approach to Understanding and Improving Research Integrity

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Abstract

Concern about the integrity of empirical research has arisen in recent years in the light of studies showing the vast majority of publications in academic journals report positive results, many of these results are false and cannot be replicated, and many positive results are the product of data dredging and the application of flexible data analysis practices coupled with selective reporting. While a number of potential solutions have been proposed, the effects of these are poorly understood and empirical evaluation of each would take many years. We propose that methods from the systems sciences be used to assess the effects, both positive and negative, of proposed solutions to the problem of declining research integrity such as study registration, Registered Reports, and open access to methods and data. In order to illustrate the potential application of systems science methods to the study of research integrity, we describe three broad types of models: one built on the characteristics of specific academic disciplines; one a diffusion of research norms model conceptualizing researchers as susceptible, “infected” and recovered; and one conceptualizing publications as a product produced by an industry comprised of academics who respond to incentives and disincentives.

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References

  • Alberts, B., Cicerone, R. J., Feinberg, S. E., Kamb, A., McNutt, M., Nerem, R. M., et al. (2015). Self-correction in science at work: Improve incentives to support research integrity. Science, 348, 1420–1422.

    Article  Google Scholar 

  • Alsheikh-Ali, A. A., Qureshi, W., Al-Mallah, M. H., & Ioannidis, J. P. A. (2011). Public availability of published research data in high-impact journals. PLoS ONE, 6(9), e24357. doi:10.1371/journal.pone.0024357.

    Article  Google Scholar 

  • American Statistical Association. (2016). ASA statement on statistical significance and p-values. The American Statistician, 70, 131–133.

    Google Scholar 

  • Anderson, C. J., Bahnik, S., Barnett-Cowan, M., Bosco, F. A., Chandler, J., Chartier, C.R. et al. (2015). Response to Comment on “Estimating the reproducibility of psychological science.” Science, 351, 1037-c. doi: 10.1126/science.aad9163.

  • Bateman, I., Kahneman, D., Munro, A., Starmer, C., & Sugden, R. (2005). Testing competing models of loss aversion: An adversarial collaboration. Journal of Public Economics, 89, 1561–1580.

    Article  Google Scholar 

  • Begley, C. G., & Ioannidis, J. P. A. (2015). Reproducibility in science: Improving the standard for basic and preclinical research. Circulation Research, 116, 116–125.

    Article  Google Scholar 

  • Benchimol, E. I., Smeeth, L., Guttman, A., Harron, K., Mohor, D., Petersen, I., et al. (2015). The Reporting of studies Conducted using Observational Routinely-collected health data (RECORD) Statement. PLoS Medicine, 12(1), e1001885.

    Article  Google Scholar 

  • Bender, M. E., Edwards, S., von Philipsborn, P., Steinbeis, F., Keil, T., & Tinnemann, P. (2015). Using co-authorship networks to map and analyse global neglected tropical disease research with an affiliation to Germany. PLoS Neglected Tropical Disease, 9(12), e0004182.

    Article  Google Scholar 

  • Benjamin, D. J., Berger, J. O., Johannesson, M., Nosek, B. A., Waggenmakers, E.-J., Berk, R., et al. (2017). Redefine statistical significance. PsyArXiv Preprints, https://psyarxiv.com/mky9j. doi: 10.17605/OSF.IO/MKY9 J.

  • Bero, L. A., & Rennie, D. (1996). Influences on the quality of published drug studies. International Journal of Technilogical Assessment in Health Care, 12, 209–237.

    Article  Google Scholar 

  • Best, A., Clark, P. I., Leischow, S. J., & Trochim, W. M. K. (2007). Greater than the Sum: Systems Thinking in Tobacco Control. National Cancer Institute, U.S. Department of Health and Human Services, National Institutes of Health.

  • Bettencourt, L. M. A., Clinton-Arias, A., Kaiser, D. I., & Castillo-Chavez, C. (2006). The power of a good idea: quantitative modeling of the spread of ideas from epidemiological models. Physica A, 364, 513–536.

    Article  Google Scholar 

  • BioMed Central (2016). Publish your study protocol. Retrieved from http://old.biomedcentral.com/authors/protocol.

  • Cadsby, C. B., Croson, R., Marks, M., & Maynes, E. (2008). Step return versus net reward in the voluntary provision of a threshold public good: An adversarial collaboration. Public Choice, 135, 277–289.

    Article  Google Scholar 

  • Center for Open Science. Registered Reports: Peer review before results are known to align scientific values and practices. Journals that have adopted Registered Reports. https://cos.io/rr/?_ga=1.126554573.139903688.1493654853 Accessed September 6, 2017.

  • Chambers, C. D., Feredoes, E., Muthukumaraswamy, S. D., & Etchells, P. J. (2014). Instead of “playing the game” it is time to change the rules: Registered Reports at AIMS Neuroscience and beyond. AIMS Neuroscience, 1, 4–17.

    Article  Google Scholar 

  • Clemens, M. A. (2017). The meaning of failed replications: A review and proposal. Journal of Economic Surveys, 31, 326–342.

    Article  Google Scholar 

  • ClinicalTrials.gov (2017). Disclaimer. https://clinicaltrials.gov/ct2/about-site/disclaimer. Accessed September 4, 2017.

  • Cope, M. B., & Allison, D. B. (2010). White hat bias: Examples of its presence in obesity research and a call for renewed commitment to faithfulness in research reporting. International Journal of Obesity, 34, 84–88.

    Article  Google Scholar 

  • Coyne, J. C., & de Voogd, J. N. (2012). Are we witnessing the decline effect in the Type D personality literature? What can be learned? Journal of Psychosomatic Research, 73, 40107.

    Google Scholar 

  • Dutilh, G., Vandekerckhove, J., Ly, A., Matzke, D., Pedroni, A., Frey, R., et al. (2017). A test of the diffusion model explanation for the worst performance rule using preregistration and blinding. Attention, Perception, and Psychophysics, 79, 713–725.

    Article  Google Scholar 

  • Edwards, M. A., & Roy, S. (2017). Academic research in the 21st century: Maintaining scientific integrity in a climate of perverse incentives and hypercompetition. Environmental Engineering Science, 34, 51–61.

    Article  Google Scholar 

  • Eisner, M. (2009). No effect in independent prevention trials: Can we reject the cynical view? Journal of Experimental Criminology, 5, 163–183.

    Article  Google Scholar 

  • Elkins, A. D., & Gorman, D. M. (2014). Systems theory in public health. In D. McQueen (Ed.) Oxford Bibliographies in Public Health. New York: Oxford University Press.

  • Epstein, J. M., Parker, J., Cummings, D., & Hammond, R. A. (2008). Coupled dynamics of fear and disease: Mathematical and computational explorations. PLoS ONE, 3(12), e3955.

    Article  Google Scholar 

  • Etz, A., & Vandekerckhove, J. (2016). A Bayesian perspective on the Reproducibility Project: Psychology. PLoS ONE, 11(2), e0149794. doi:10.1371/journal.pone.0149794.

    Article  Google Scholar 

  • Fanelli, D. (2009). How many scientists fabricate and falsify research? A systematic review and meta-analysis of survey data. PLoS ONE, 4(5), e5738.

    Article  Google Scholar 

  • Fanelli, D. (2010a). Negative results are disappearing from most disciplines and countries. Scientometrics, 90, 891–904.

    Article  Google Scholar 

  • Fanelli, D. (2010b). Do pressures to publish increase scientists’ bias? An empirical support for US States data. PLoS ONE, 5(4), e10271. doi:10.1371/journal.pone.0010271.

    Article  Google Scholar 

  • Fanelli, D. (2012). “Positive” results increase down the hierarchy of science. PLoS ONE, 4(5), e10068.

    Google Scholar 

  • Fanelli, D. (2013). Redefine misconduct as distorted reporting. Nature, 494, 149.

    Article  Google Scholar 

  • Fanelli, D. (2016). Set up a “self-retraction” system for honest errors. Nature, 531, 415.

    Article  Google Scholar 

  • Fannelli, D. (2013). Positive results receive more citations, but only in some disciplines. Scientometrics, 94, 701–709.

    Article  Google Scholar 

  • Ferguson, C. J., & Heene, M. (2012). A vast graveyard of undead theories: Publication bias and psychological science’s aversion to the null. Perspectives on Psychological Science, 7, 555–561.

    Article  Google Scholar 

  • Fleming, P. S., Koletsi, D., Dwan, K., & Pamdis, N. (2015). Outcome discrepancies and selective reporting: Impacting the leading journals? PLoS ONE, 10(5), e0127495. doi:10.1371/journal.pone.0127495.

    Article  Google Scholar 

  • Fonesca, B. P. F., Sampoaio, R. B., Fonseca, M. V. A., & Zicker, F. (2016). Co-authorship network analysis in health research: Method and potential use. Health Research Policy and Systems, 14, 34.

    Article  Google Scholar 

  • Fucci, D., Scanniello, G., Ramano, S., Shepperd, M., Sigweni, B., Uyaguari, F., et al. (2016). An external replication on the effects of test-driven development using a multi-site blind analysis approach. In ESEM’16: Proceedings of the 10 th ACM/IEEE International Symposium on Empirical Software and Measurement. Article No. 3 http://people.brunel.ac.uk/~csstmms/FucciEtAl_ESEM2016.pdf.

  • Ghimire, S., Kyung, E., Kang, W., & Kim, E. (2012). Assessment of adherence to the CONSORT Statement for quality of reports on randomized controlled trial abstracts from four high-impact general medical journals. Trials, 13, 77. doi:10.1186/1745-6215-13-77.

    Article  Google Scholar 

  • Gilbert, D. T., King. G., Pettigrew, S., & Wilson, T. D. (2015). Comment on “Estimating the reproducibility of psychological science.” Science, 351, 1037–b. doi: 10.1126/science.aad7243.

  • Goodman, S. N., Fanelli, D., & Ioannidis, J. P. A. (2016). What does research reproducibility mean? Science Translational Medicine, 8, 341, ps12.

  • Gorman, D. M. (2016). Can we trust positive findings of intervention research? The role of conflict of interest. Prevention Science. April 23 (Epub ahead of print).

  • Gorman, D. M. (2017a). The decline effect in evaluations of the impact of the Strengthening Families Program for Youth 10-14 (SFP 10-14) on adolescent substance use. Children and Youth Services Review, 81, 29–39.

    Article  Google Scholar 

  • Gorman, D. M. (2017b). Has the National Registry of Evidence-based Programs and Practices (NREPP) lost its way? International Journal of Drug Policy, 45, 40–41.

    Article  Google Scholar 

  • Gorman, D. M. (2017c). Evidence-based practice as a driver of pseudoscience in prevention research. In A. B. Kaufman & J. Kaufman (Eds.), Pseudoscience. Cambridge: MIT Press.

    Google Scholar 

  • Hay, M., Andrews, M., Wilson, R., Callender, D., O’Malley, P. G., & Douglas, K. (2016). Reporting quality of randomized controlled abstracts among high-impact general medical journals: A review and analysis. British Medical Journal Open, 6(7), e011082. doi:10.1136/bmjopen-2016-011082.

    Google Scholar 

  • Hirsch, G. B., Levine, R., & Miller, R. L. (2007). Using system dynamics modeling to understand the impact of social change initiatives. American Journal of Community Psychology, 39, 239–253.

    Article  Google Scholar 

  • Holder, H. D. (2010). Prevention programs in the 21st century: What we do not discuss in public. Addiction, 105, 578–581.

    Article  Google Scholar 

  • Humphreys, M., de la Sierra, R. S., & van der Windt, P. (2013). Fishing, commitment, and communication: A proposal for comprehensive nonbinding research registration. Political Analysis, 21, 1–20.

    Article  Google Scholar 

  • Ioannidis, J. P. A. (2005). Why most published research findings are false. PLos Med, 2(8), e124.

    Article  Google Scholar 

  • Ioannidis, J. P. A. (2008). Why most published research findings are false. PLoS Medicine, 2, e124 (0696–0701).

  • Ioannidis, J. P. A. (2012). Scientific inbreeding and same-team replication: Type D personality as an example. Journal of Psychosomatic Research, 73, 408–410.

    Article  Google Scholar 

  • Ioannidis, J. P. A. (2014). How to make more published research true. PLoS Medicine, 11(10), 1001747.

    Article  Google Scholar 

  • Ioannidis, J. P. A. (2016). Evidence-based medicine has been hijacked: A report to David Sackett. Journal of Clinical Epidemiology, 73, 82–84.

    Article  Google Scholar 

  • Ioannidis, J. P. A., Greenland, S., Hlatky, M. A., Khoury, M. J., Macleod, M. R., Moher, D., et al. (2014a). Increasing value and reducing waste in research design, conduct, and analysis. Lancet, 383, 166–175.

    Article  Google Scholar 

  • Ioannidis, J. P. A., Munafo, M. R., Fusar-Poli, P., Nosek, B. A., & David, S. P. (2014b). Publication and other reporting biases in cognitive sciences: Detection, prevalence, and prevention. Trends in Cognitive Sciences, 18, 235–241.

    Article  Google Scholar 

  • Ioannidis, J. P. A., Tarone, R., & McLaughlin, J. K. (2011). The false-positive to false-negative ratio in epidemiologic studies. Epidemiology, 22(4), 450–456.

    Article  Google Scholar 

  • Johnson, V. E. (2013). Revised standards for statistical evidence. Proceedings of the National Academy of Science, 110(48), 19313–19317. doi:10.1073/pnas.1313476110.

    Article  Google Scholar 

  • Kerr, N. L. (1998). HARKing: Hypothesizing after the results are known. Personality and Social Psychology Review, 2, 196–217.

    Article  Google Scholar 

  • Klein, J. R., & Roodman, A. (2005). Blind analysis in nuclear and particle physics. Annual Review of Nuclear and Particle Science, 55, 141–163.

    Article  Google Scholar 

  • Kovanis, M., Porcher, R., Ravaud, P., & Trinquart, L. (2015). Complex systems approaches to scientific publication and peer-review system: Development of an agent-based model calibrated with empirical journal data. Scientometrics, 106, 695–715.

    Article  Google Scholar 

  • Kücük, B., Güler, N, & Eskici, B. (2008). A dynamic simulation model of academic publications and citations. In Proceedings of the 26th International Conference of the System Dynamics Society. Athens, Greece. Retrieved from https://www.systemdynamics.org/conferences/2008/proceed/papers/KUCUK339.pdf.

  • Laura & John Arnold Foundation. (2016). Grants. Retrieved September 5, 2017 from http://www.arnoldfoundation.org/grants/.

  • Luke, D. A., & Stamatikis, K. A. (2012). Systems science methods in public health: Dynamics, networks, and agents. Annual Review of Public Health, 33, 357–376.

    Article  Google Scholar 

  • MacCoun, R., & Perlmutter, S. (2015). Hide results to seek the truth. Nature, 526, 187–189.

    Article  Google Scholar 

  • MacCoun, R., & Perlmutter, S. (2017). Blind analysis as a corrective for confirmatory biasin physics and psychology. In S. O. Lilienfeld & I. Waldman (Eds.), Psychological Science under Scrutiny: Recent Challenges and Proposed Solutions. Wiley-Blackwell: Hoboken.

    Google Scholar 

  • Matzke, D., Nieuwenhuis, S., van Rijn, H., Slagter, H. A., van der Molen, M. W., & Wagenmakers, E.-J. (2015). The effect of horizontal eye movements on free recall: A preregistered adversarial collaboration. Journal of Experimental Psychology: General, 144, e1–e15.

    Article  Google Scholar 

  • McElreath, R., & Smaldino, P. E. (2015). Replication, communication, and the population dynamics of scientific discovery. PLoS ONE, 10(8), e0136088.

    Article  Google Scholar 

  • Melander, H., Ahlqvist-Rastad, J., Meijer, G., & Beermann, B. (2003). Evidence b(i)ased medicine—Selective reporting from studies sponsored by pharmaceutical industry: review of studies in new drug applications. British Medical Journal, 326, 1171–1175.

    Article  Google Scholar 

  • Mellers, B., Hertwig, R., & Kahneman, D. (2001). Do frequency representations eliminate conjunction effects? An exercise in adversarial collaboration. Psychological Science, 12, 269–275.

    Article  Google Scholar 

  • Miguel, E., Camerer, C., Casey, K., Cohen, J., Esterling, K. M., Gerber, A., et al. (2014). Promoting transparency in social science research. Science, 343, 30–31.

    Article  Google Scholar 

  • Nosek, B. A., Alter, G., Banks, G. C., Borsboom, D., Bowman, S. D., Breckler, S. J., et al. (2015). Promoting an open research culture. Science, 348, 1422–1425.

    Article  Google Scholar 

  • Nosek, B. A., & Lakens, D. (2014). Registered reports: A method to increase the credibility of published results. Social Psychology, 45, 137–141.

    Article  Google Scholar 

  • Nosek, B. A., Spies, J. R., & Motyl, M. (2012). Scientific Utopia II. Restructuring incentives and practices to promote truth over publishability. Psychological Science, 7, 615–631.

    Google Scholar 

  • Nuzzo, R. (2015). Fooling ourselves. Science, 526, 182–185.

    Google Scholar 

  • Open Science Collaboration (2015). Estimating the reproducibility of psychological science. Science, 349, acac4716.

  • Rahmandad, H., & Sterman, J. (2008). Heterogeneity and network structure in the dynamics of diffusion: Comparing agent-based and differential equation models. Management Science, 54, 998–1014.

    Article  Google Scholar 

  • Satpute, S., Mehta, M., Bhete, S., & Kurle, D. (2016). Assessment of adherence to the statistical components of Consolidated Standards of Reporting Trials Statement for quality of reports on randomized controlled trials from five pharmacology journals. Perspectives in Clinical Research, 7, 128–131.

    Article  Google Scholar 

  • Schlitz, M., Wiseman, R., Watt, C., & Radin, D. (2006). Of two minds: Skeptic-proponent collaboration with parapsychology. British Journal of Psychology, 97, 313–322.

    Article  Google Scholar 

  • Schulz, K.F., Altman, D.G., Moher, D., & CONSORT Group. (2010). CONSORT 2010 Statement: updated guidelines for reporting parallel group randomised trials. BMC Medicine, 18, 18. doi:10.1186/1741-7015-8-18.

    Google Scholar 

  • Simmons, J. P., Nelson, L. D., & Simonsohn, U. (2011). False-positive psychology: Undisclosed flexibility in data collection and analysis allows presenting anything as significant. Psychological Science, 22, 1359–1366.

    Article  Google Scholar 

  • Smaldino & McElreath. (2016). The natural selection of bad science. Royal Society Open Science, 3, 160384. doi:10.1098/rsos.160384.

    Article  Google Scholar 

  • Sterman, J. D. (2000). Business Dynamics: Systems Thinking and Modeling for a Complex World. Boston: Irwin/McGraw Hill.

    Google Scholar 

  • Sterman, J. D. (2006). Learning from evidence in a complex world. American Journal of Public Health, 96, 505–514.

    Article  Google Scholar 

  • Sterman, J. D., & Wittenberg, J. (1999). Path dependence, competition, and succession in the dynamics of scientific revolution. Organizational Science, 10, 322–341.

    Article  Google Scholar 

  • Szucs, D., & Ioannidis, J. P. A. (2017). When null hypothesis significance testing is unsuitable for research: A reassessment. Frontiers in Human Neuroscience, 11, 390. doi:10.3389/fnhum.2017.00390.

    Article  Google Scholar 

  • Walker, K. F., Stevenson, G., & Thornton, J. G. (2014). Discrepencies between registration and publication of randomised controlled trias: An observational study. Journal of the Royal Society of Medicine Open, 5(5), 1–4.

    Google Scholar 

  • Yong, E. (2012). Replication studies: Bad copy. Nature, 485, 298–300.

    Article  Google Scholar 

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Authors and Affiliations

  1. Department of Epidemiology and Biostatistics, Texas A&M University, TAMU 1266, College Station, TX, 77843-1266, USA

    Dennis M. Gorman

  2. Department of Industrial and Systems Engineering, Texas A&M University, College Station, TX, 77843-1266, USA

    Amber D. Elkins & Mark Lawley

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  1. Dennis M. Gorman
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Correspondence to Dennis M. Gorman.

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Gorman, D.M., Elkins, A.D. & Lawley, M. A Systems Approach to Understanding and Improving Research Integrity. Sci Eng Ethics 25, 211–229 (2019). https://doi.org/10.1007/s11948-017-9986-z

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