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Using General Messages to Persuade on a Politicized Scientific Issue

Published online by Cambridge University Press:  24 October 2022

Jon Green*
Affiliation:
Northeastern University, Boston, USA Harvard Kennedy School, Cambridge, USA
James N. Druckman
Affiliation:
Northwestern University, Evanston, USA
Matthew A. Baum
Affiliation:
Harvard Kennedy School, Cambridge, USA
David Lazer
Affiliation:
Northeastern University, Boston, USA
Katherine Ognyanova
Affiliation:
Rutgers, The State University of New Jersey, New Brunswick, USA
Matthew D. Simonson
Affiliation:
University of Pennsylvania, Philadelphia, USA
Jennifer Lin
Affiliation:
Northwestern University, Evanston, USA
Mauricio Santillana
Affiliation:
Northeastern University, Boston, USA Harvard Medical School, Boston, USA
Roy H. Perlis
Affiliation:
Harvard Medical School, Boston, USA
*
*Corresponding author. Email: jo.green@northeastern.edu

Abstract

Politics and science have become increasingly intertwined. Salient scientific issues, such as climate change, evolution, and stem-cell research, become politicized, pitting partisans against one another. This creates a challenge of how to effectively communicate on such issues. Recent work emphasizes the need for tailored messages to specific groups. Here, we focus on whether generalized messages also can matter. We do so in the context of a highly polarized issue: extreme COVID-19 vaccine resistance. The results show that science-based, moral frame, and social norm messages move behavioral intentions, and do so by the same amount across the population (that is, homogeneous effects). Counter to common portrayals, the politicization of science does not preclude using broad messages that resonate with the entire population.

Type
Letter
Copyright
Copyright © The Author(s), 2022. Published by Cambridge University Press

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References

Akin, H and Scheufele, DA (2017) Overview of the science of science communication. In Jamieson, KH, Kahan, DM and Scheufele, DA (eds), The Oxford Handbook of the Science of Science Communication. Oxford, UK: Oxford University Press, 2533.Google Scholar
Athey, S, Tibshirani, J, and Wager, S (2019) Generalized random forests. The Annals of Statistics 47(2), 11481178.CrossRefGoogle Scholar
Bayes, R et al. (2020) When and how different motives can drive motivated political reasoning. Political Psychology 41(5), 10311052.CrossRefGoogle Scholar
Bokemper, SE et al. (2021) Persuading U.S. White evangelicals to vaccinate for COVID-19: testing message effectiveness in fall 2020 and spring 2021. Proceedings of the National Academy of Sciences 118(49), e2114762118.Google Scholar
Bolsen, T and Druckman, JN (2015) Counteracting the politicization of science. Journal of Communication 65(5), 745769.CrossRefGoogle Scholar
Bolsen, T and Druckman, JN (2018) Do partisanship and politicization undermine the impact of a scientific consensus message about climate change? Group Processes & Intergroup Relations 21(3), 389402.CrossRefGoogle Scholar
Breiman, L (2001) Random forests. Machine Learning 45, 532.CrossRefGoogle Scholar
Bretz, F, Hothorn, T, and Westfall, P (2011) Multiple Comparisons Using R. Boca Raton, USA: Chapman & Hall/CRC Press. Available from http://www.ievbras.ru/ecostat/Kiril/R/Biblio_N/R_Eng/Bretz2011.pdfGoogle Scholar
Brewer, NT et al. (2017) Increasing vaccination: putting psychological science into action. Psychological Science in the Public Interest 18(3), 149207.CrossRefGoogle ScholarPubMed
Callaghan, T et al. (2019) Parent psychology and the decision to delay childhood vaccination. Social Science & Medicine 238, 112407.CrossRefGoogle ScholarPubMed
Callaghan, T et al. (2021) Correlates and disparities of intention to vaccinate against COVID-19. Social Science & Medicine 272, 113638.CrossRefGoogle ScholarPubMed
Cialdini, RB (2007) Descriptive social norms as underappreciated sources of social control. Psychometrika 72(2), 263.CrossRefGoogle Scholar
Clinton, J et al. (2021) Partisan pandemic: how partisanship and public health concerns affect individuals’ social mobility during COVID-19. Science Advances 7(2), eabd7204.CrossRefGoogle Scholar
Coppock, A, Leeper, TJ, and Mullinix, KJ (2018) Generalizability of heterogeneous treatment effect estimates across samples. Proceedings of the National Academy of Sciences 115(49), 1244112446.CrossRefGoogle ScholarPubMed
Druckman, JN (2017) The crisis of politicization within and beyond science. Nature Human Behaviour 1(9), 615617.CrossRefGoogle ScholarPubMed
Druckman, JN and Lupia, A (2017) Using frames to make scientific communication more effective. In Jamieson KH, Kahan DM and Scheufele DA (eds), The Oxford Handbook of the Science of Science Communication, Oxford, UK: Oxford University Press 351360.Google Scholar
Druckman, JN et al. (2021) Affective polarization, local contexts and public opinion in America. Nature Human Behaviour 5(1), 2838.CrossRefGoogle ScholarPubMed
Dwyer, PC, Maki, A, and Rothman, AJ (2015) Promoting energy conservation behavior in public settings: the influence of social norms and personal responsibility. Journal of Environmental Psychology 41, 3034.CrossRefGoogle Scholar
Feinberg, M and Willer, R (2013) The moral roots of environmental attitudes. Psychological Science 24(1), 5662.CrossRefGoogle ScholarPubMed
Feinberg, M and Willer, R (2019) Moral reframing: a technique for effective and persuasive communication across political divides. Social and Personality Psychology Compass 13(12), e12501.CrossRefGoogle Scholar
Gauchat, G (2012) Politicization of science in the public sphere: a study of public trust in the United States, 1974 to 2010. American Sociological Review 77(2), 167187.CrossRefGoogle Scholar
Gollwitzer, A et al. (2020) Partisan differences in physical distancing are linked to health outcomes during the COVID-19 pandemic. Nature Human Behaviour 4(11), 11861197.CrossRefGoogle ScholarPubMed
Green, J et al. (2020) Elusive consensus: polarization in elite communication on the COVID-19 pandemic. Science Advances 6(28), eabc2717.CrossRefGoogle ScholarPubMed
Green, J et al. (2022) “Replication data for Using General Messages to Persuade on a Politicized Scientific Issue”, https://doi.org/10.7910/DVN/4QEWQK, Harvard Dataverse, V1, UNF:6:qyEolLT87WHe2I+p9etQAA== [fileUNF]CrossRefGoogle Scholar
Hegland, A et al. (forthcoming) A partisan pandemic: how COVID-19 was primed for polarization. The Annals of the American Academy of Political and Social Science 700(1), 5572.CrossRefGoogle Scholar
Hersh, ED and Schaffner, BF (2013) Targeted campaign appeals and the value of ambiguity. The Journal of Politics 75(2), 520534.CrossRefGoogle Scholar
Jaeger, CM and Schultz, PW (2017) Coupling social norms and commitments: testing the underdetected nature of social influence. Journal of Environmental Psychology 51(3), 199208.CrossRefGoogle Scholar
Kahan, DM (2015) Climate-science communication and the measurement problem. Political Psychology 36, 143.CrossRefGoogle Scholar
Lazer, D et al. (2021) Report #43: COVID-19 Vaccine Rates and Attitudes among Americans. Available from https://osf.io/v6qbx/CrossRefGoogle Scholar
Lee, JJ (2021) Party polarization and trust in science: what about democrats? Socius 7, 112.CrossRefGoogle Scholar
Lunz Trujillo, K et al. (2020) Correcting misperceptions about the MMR vaccine: using psychological risk factors to inform targeted communication strategies. Political Research Quarterly 74(2), 464478.CrossRefGoogle Scholar
Macedo, S (2019) Introduction. In Oreskes, N (ed.), Why Trust Science? Princeton, USA: Princeton University Press.Google Scholar
Merkley, E (2020) Anti-intellectualism, populism, and motivated resistance to expert consensus. Public Opinion Quarterly 84(1), 114.CrossRefGoogle Scholar
Moehring, A et al. (2022) Providing normative information increases intentions to accept a COVID-19 vaccine. Working paper. Available from https://psyarxiv.com/srv6t/.CrossRefGoogle Scholar
Motta, M et al. (2021) Encouraging COVID-19 vaccine uptake through effective health communication. Frontiers in Political Science 3, 1.CrossRefGoogle Scholar
National Academies of Sciences, Engineering, and Medicine (2017) Communicating Science Effectively: A Research Agenda. Washington, District of Columbia, USA: National Academies Press (US).Google Scholar
Nature (2010) Science scorned. Nature 467(7312), 133. https://doi.org/10.1038/467133a.CrossRefGoogle Scholar
Palm, R, Bolsen, T, and Kingsland, JT (2021) The effect of frames on COVID-19 vaccine resistance. Frontiers in Political Science 3, 41.CrossRefGoogle Scholar
Pickup, M, Kimbrough, EO, and de Rooij, EA (2021) Expressive politics as (costly) norm following. Political Behavior, 121.Google Scholar
Pink, SL et al. (2021) Elite party cues increase vaccination intentions among Republicans. Proceedings of the National Academy of Sciences 118(32), e2106559118.CrossRefGoogle ScholarPubMed
Raymond, L, Kelly, D, and Hennes, E (2021) Norm-based governance for a new era: collective action in the face of hyper-politicization. Perspectives on Politics, First View, 114.Google Scholar
Uslu, A et al. (2021) Report #63: The Decision to Not Get Vaccinated, from the Perspective of the Unvaccinated. Available from https://osf.io/fazup/CrossRefGoogle Scholar
Van der Linden, SL et al. (2015) The scientific consensus on climate change as a gateway belief: experimental evidence. PloS one 10(2), e0118489.CrossRefGoogle ScholarPubMed
Wager, S and Athey, S (2018) Estimation and inference of heterogeneous treatment effects using random forests. Journal of the American Statistical Association 113(523), 12281242.CrossRefGoogle Scholar
Wolsko, C, Ariceaga, H, and Seiden, J (2016) Red, white, and blue enough to be green: effects of moral framing on climate change attitudes and conservation behaviors. Journal of Experimental Social Psychology 65, 719.CrossRefGoogle Scholar
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