Effective strategies for rebutting science denialism in public discussions

Abstract

Science deniers question scientific milestones and spread misinformation, contradicting decades of scientific endeavour. Advocates for science need effective rebuttal strategies and are concerned about backfire effects in public debates. We conducted six experiments to assess how to mitigate the influence of a denier on the audience. An internal meta-analysis across all the experiments revealed that not responding to science deniers has a negative effect on attitudes towards behaviours favoured by science (for example, vaccination) and intentions to perform these behaviours. Providing the facts about the topic or uncovering the rhetorical techniques typical for denialism had positive effects. We found no evidence that complex combinations of topic and technique rebuttals are more effective than single strategies, nor that rebutting science denialism in public discussions backfires, not even in vulnerable groups (for example, US conservatives). As science deniers use the same rhetoric across domains, uncovering their rhetorical techniques is an effective and economic addition to the advocates’ toolbox.

Access options

Rent or Buy article

Get time limited or full article access on ReadCube.

from$8.99

All prices are NET prices.

Fig. 1: 5 × 5 matrix of rebutting science denialism in public discussions about vaccination.
Fig. 2: Effects of denial and rebuttals on intention to perform a behaviour favoured by science.
Fig. 3: Technique rebuttal and topic rebuttal mitigate the influence of the science denier.
Fig. 4: No evidence that the combination of topic and technique rebuttal is more effective than the single strategies.
Fig. 5: Effect of confidence in vaccination on changes in attitude and intention.
Fig. 6: Effect of political ideology on changes in attitude and intention.

Data availability

The data supporting the findings of this study are available from the Open Science Framework (https://doi.org/10.17605/OSF.IO/XX2KT)57.

Code availability

The syntax used to analyse the datasets in this study is available from the Open Science Framework (https://doi.org/10.17605/OSF.IO/XX2KT)57.

References

  1. 1.

    Vaccines and immunization. World Health Organization http://www.euro.who.int/en/health-topics/disease-prevention/vaccines-and-immunization/vaccines-and-immunization/vaccine-quality,-efficacy-and-safety (2018).

  2. 2.

    Causes of Climate Change Climate Action. https://ec.europa.eu/clima/change/causes_en (European Commission, 2018).

  3. 3.

    Teaching of Evolution: Fact and Theory https://www.acs.org/content/acs/en/policy/publicpolicies/education/evolution.html (American Chemical Society, 2017).

  4. 4.

    Carmichael, J. T., Brulle, R. J. & Huxster, J. K. The great divide: understanding the role of media and other drivers of the partisan divide in public concern over climate change in the USA, 2001–2014. Clim. Change 141, 599–612 (2017).

    Article  Google Scholar 

  5. 5.

    Mildenberger, M. & Leiserowitz, A. Public opinion on climate change: is there an economy–environment tradeoff? Env. Polit. 26, 801–824 (2017).

    Article  Google Scholar 

  6. 6.

    Lewandowsky, S., Ecker, U. K. H. & Cook, J. Beyond misinformation: understanding and coping with the “post-truth” era. J. Appl. Res. Mem. Cogn. 6, 353–369 (2017).

    Article  Google Scholar 

  7. 7.

    Chigwedere, P., Seage, G. R., Gruskin, S., Lee, T.-H. & Essex, M. Estimating the lost benefits of antiretroviral drug use in South Africa. J. Acquir. Immune Defic. Syndr. 49, 410–415 (2008).

    Article  Google Scholar 

  8. 8.

    Flaherty, D. K. The vaccine-autism connection: a public health crisis caused by unethical medical practices and fraudulent science. Ann. Pharmacother. 45, 1302–1304 (2011).

    Article  Google Scholar 

  9. 9.

    Lewandowsky, S., Ballard, T., Oberauer, K. & Benestad, R. A blind expert test of contrarian claims about climate data. Glob. Environ. Change 39, 91–97 (2016).

    Article  Google Scholar 

  10. 10.

    Björnberg, K. E., Karlsson, M., Gilek, M. & Hansson, S. O. Climate and environmental science denial: a review of the scientific literature published in 1990–2015. J. Clean. Prod. 167, 229–241 (2018).

    Article  Google Scholar 

  11. 11.

    Dunlap, R. E. Climate Change skepticism and denial: An introduction. Am. Behav. Sci. 57, 691–698 (2013).

    Article  Google Scholar 

  12. 12.

    Ziman, J. Is science losing its objectivity? Nature 382, 751–754 (1996).

    CAS  Article  Google Scholar 

  13. 13.

    Diethelm, P. & McKee, M. Denialism: what is it and how should scientists respond? Eur. J. Public Health 19, 2–4 (2009).

    Article  Google Scholar 

  14. 14.

    Lewandowsky, S. & Oberauer, K. Motivated rejection of science. Curr. Dir. Psychol. Sci. 25, 217–222 (2016).

    Article  Google Scholar 

  15. 15.

    Hornsey, M. J. & Fielding, K. S. Attitude roots and jiu jitsu persuasion: understanding and overcoming the motivated rejection of science. Am. Psychol. 72, 459–473 (2017).

    Article  Google Scholar 

  16. 16.

    Oreskes, N. & Conway, E. M. Defeating the merchants of doubt. Nature 465, 686–687 (2010).

    CAS  Article  Google Scholar 

  17. 17.

    Betsch, C. Advocating for vaccination in a climate of science denial. Nat. Microbiol. 2, 17106 (2017).

    CAS  Article  Google Scholar 

  18. 18.

    Williamson, P. Take the time and effort to correct misinformation. Nature 540, 171 (2016).

    Article  Google Scholar 

  19. 19.

    Cockrell, M., Dubickas, K., Hepner, M., Ilich, A. & McCarthy, M. Embracing advocacy in science. Fisheries 43, 179–182 (2018).

    Article  Google Scholar 

  20. 20.

    van der Linden, S., Leiserowitz, A., Rosenthal, S. & Maibach, E. Inoculating the public against misinformation about climate change. Glob. Chall. 1, 1600008 (2017).

    Article  Google Scholar 

  21. 21.

    Cook, J., Lewandowsky, S. & Ecker, U. K. H. Neutralizing misinformation through inoculation: exposing misleading argumentation techniques reduces their influence. PLoS One 12, e0175799 (2017).

    Article  Google Scholar 

  22. 22.

    Lewandowsky, S., Ecker, U. K. H., Seifert, C. M., Schwarz, N. & Cook, J. Misinformation and its correction: continued influence and successful debiasing. Psychol. Sci. Public Interest 13, 106–131 (2012).

    Article  Google Scholar 

  23. 23.

    Ecker, U. K. H., Hogan, J. L. & Lewandowsky, S. Reminders and repetition of misinformation: helping or hindering its retraction? J. Appl. Res. Mem. Cogn. 6, 185–192 (2017).

    Article  Google Scholar 

  24. 24.

    Schmid, P., MacDonald, N. E., Habersaat, K. & Butler, R. Commentary to: how to respond to vocal vaccine deniers in public. Vaccine 36, 196–198 (2018).

    Article  Google Scholar 

  25. 25.

    Benoit, W. L., Hansen, G. J. & Verser, R. M. A meta-analysis of the effects of viewing U.S. presidential debates. Commun. Monogr. 70, 335–350 (2003).

    Article  Google Scholar 

  26. 26.

    Vosoughi, S., Roy, D. & Aral, S. The spread of true and false news online. Science 359, 1146–1151 (2018).

    CAS  Article  Google Scholar 

  27. 27.

    Seiter, J., Weger, H., Jensen, A. & Kinzer, H. The role of background behavior in televised debates: does displaying nonverbal agreement and/or disagreement benefit either debater? J. Soc. Psychol. 150, 278–300 (2010).

    Article  Google Scholar 

  28. 28.

    Nyhan, B. & Reifler, J. Does correcting myths about the flu vaccine work? An experimental evaluation of the effects of corrective information. Vaccine 33, 459–464 (2015).

    Article  Google Scholar 

  29. 29.

    Nyhan, B. & Reifler, J. When corrections fail: the persistence of political misperceptions. Polit. Behav. 32, 303–330 (2010).

    Article  Google Scholar 

  30. 30.

    Cook, J. & Lewandowsky, S. Rational irrationality: modeling climate change belief polarization using Bayesian networks. Top. Cogn. Sci. 8, 160–179 (2016).

    Article  Google Scholar 

  31. 31.

    Best Practice Guidance: How to Respond to Vocal Vaccine Deniers in Public (World Health Organization Regional Office for Europe, 2016).

  32. 32.

    Cacioppo, J. T., Petty, R. E. & Morris, K. J. Effects of need for cognition on message evaluation, recall, and persuasion. J. Pers. Soc. Psychol. 45, 805–818 (1983).

    Article  Google Scholar 

  33. 33.

    Friestad, M. & Wright, P. The persuasion knowledge model: how people cope with persuasion attempts. J. Consum. Res. 21, 1–31 (1994).

    Article  Google Scholar 

  34. 34.

    Pornpitakpan, C. The persuasiveness of source credibility: a critical review of five decades’ evidence. J. Appl. Soc. Psychol. 34, 243–281 (2004).

    Article  Google Scholar 

  35. 35.

    Chaiken, S. Heuristic versus systematic information processing and the use of source versus message cues in persuasion. J. Pers. Soc. Psychol. 39, 752–766 (1980).

    Article  Google Scholar 

  36. 36.

    Hronikx, J. A review of experimental research on the relative persuasiveness of anecdotal, statistical, causal, and expert evidence. Stud. Commun. Sci. 5, 205–216 (2005).

    Google Scholar 

  37. 37.

    Allen, M. Meta‐analysis comparing the persuasiveness of one‐sided and two‐sided messages. West. J. Speech Commun. 55, 390–404 (1991).

    Article  Google Scholar 

  38. 38.

    O’Keefe, D. J. How to handle opposing arguments in persuasive messages: a meta-analytic review of the effects of one-sided and two-sided messages. Ann. Int. Commun. Assoc. 22, 209–249 (1999).

    Article  Google Scholar 

  39. 39.

    Cook, J. & Lewandowsky, S. The Debunking Handbook (University of Queensland, 2011).

  40. 40.

    Petty, R. E. & Cacioppo, J. T. The elaboration likelihood model of persuasion. Adv. Exp. Soc. Psychol. 19, 123–205 (1986).

    Google Scholar 

  41. 41.

    Eisend, M. Understanding two-sided persuasion: an empirical assessment of theoretical approaches. Psychol. Market. 24, 615–640 (2007).

    Article  Google Scholar 

  42. 42.

    Sheeran, P. et al. The impact of changing attitudes, norms, and self-efficacy on health-related intentions and behavior: a meta-analysis. Health Psychol. 35, 1178–1188 (2016).

    Article  Google Scholar 

  43. 43.

    O’Keefe, D. J. Persuasion: Theory and Research (Sage, 2002).

  44. 44.

    O’Keefe, D. J. Message generalizations that support evidence-based persuasive message design: specifying the evidentiary requirements. Health Commun. 30, 106–113 (2015).

    Article  Google Scholar 

  45. 45.

    Goh, J. X., Hall, J. A. & Rosenthal, R. Mini meta-analysis of your own studies: some arguments on why and a primer on how. Soc. Personal. Psychol. Compass 10, 535–549 (2016).

    Article  Google Scholar 

  46. 46.

    Baguley, T. Standardized or simple effect size: what should be reported? Br. J. Psychol. 100, 603–617 (2009).

    Article  Google Scholar 

  47. 47.

    Cohen, P., Cohen, J., Aiken, L. S. & West, S. G. The problem of units and the circumstance for POMP. Multivar. Behav. Res. 34, 315–346 (1999).

    Article  Google Scholar 

  48. 48.

    Leys, C., Ley, C., Klein, O., Bernard, P. & Licata, L. Detecting outliers: do not use standard deviation around the mean, use absolute deviation around the median. J. Exp. Soc. Psychol. 49, 764–766 (2013).

    Article  Google Scholar 

  49. 49.

    Anderson, T Communicating science-based messages on vaccines. Bull. World Health Organ. 95, 670–671 (2017).

    Article  Google Scholar 

  50. 50.

    van der Linden, S., Leiserowitz, A. & Maibach, E. Scientific agreement can neutralize politicization of facts. Nat. Hum. Behav. 2, 2–3 (2018).

    Article  Google Scholar 

  51. 51.

    Cook, J., Maibach, E., van der Linden, S. & Lewandowsky, S. The Consensus Handbook (Climate Change Communication, 2018).

  52. 52.

    Nsangi, A. et al. Effects of the informed health choices primary school intervention on the ability of children in Uganda to assess the reliability of claims about treatment effects: a cluster-randomised controlled trial. Lancet 390, 374–388 (2017).

    Article  Google Scholar 

  53. 53.

    Sheeran, P. Intention—behavior relations: a conceptual and empirical review. Eur. Rev. Soc. Psychol. 12, 1–36 (2002).

    Article  Google Scholar 

  54. 54.

    Berinsky, A. J., Margolis, M. F. & Sances, M. W. Separating the shirkers from the workers? Making sure respondents pay attention on self-administered surveys. Am. J. Polit. Sci. 58, 739–753 (2014).

    Article  Google Scholar 

  55. 55.

    Oreskes, N. Beware: transparency rule is a Trojan horse. Nature 557, 469 (2018).

    CAS  Article  Google Scholar 

  56. 56.

    EFS Survey, v. Spring 2016–Winter 2018 (Questback GmbH, 2016).

  57. 57.

    Schmid, P. & Betsch, C. Effective strategies for rebutting science denialism in public discussions. Preprint at OSF https://doi.org/10.17605/OSF.IO/XX2KT (2019).

  58. 58.

    Sedgwick, P. Meta-analyses heterogeneity and subgroup analysis. BMJ 346, f4040 (2013).

    Article  Google Scholar 

Download references

Acknowledgements

The authors thank B. Wippert, T. Steinke, J. Gerlach and M. Schwarzer for their help collecting the data and developing the stimulus material and L. Korn for support visualizing Fig. 2 and Supplementary Fig. 2. The authors are also grateful for the valuable input from K. Habersaat. Parts of the study were funded by grants to C.B. from the German Federal Ministry for Education and Research (BMBF) via the interdisciplinary and trans-sectoral consortium InfectControl2020 to the University of Erfurt (no. 03ZZ0819A) and the German Research Foundation to C.B. (no. BE3970/11-1). The funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript. No other funding bodies were involved.

Author information

Affiliations

Authors

Contributions

Both authors substantially contributed to this article. P.S. and C.B. developed and designed the study, conducted the analyses and wrote the Article and Supplementary Information. P.S. visualized and curated the data. C.B. secured the funding.

Corresponding author

Correspondence to Philipp Schmid.

Ethics declarations

Competing interests

The authors declare no competing interests.

Additional information

Peer review information: Primary Handling Editor: Aisha Bradshaw.

Publisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary information

Supplementary Information

Supplementary Methods, Supplementary Results, Supplementary References, Supplementary Figures 1–4, and Supplementary Tables 1–17.

Reporting Summary

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Schmid, P., Betsch, C. Effective strategies for rebutting science denialism in public discussions. Nat Hum Behav 3, 931–939 (2019). https://doi.org/10.1038/s41562-019-0632-4

Download citation

Further reading