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Toolbox of individual-level interventions against online misinformation

Nature Human Behaviour (2024)Cite this article

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Abstract

The spread of misinformation through media and social networks threatens many aspects of society, including public health and the state of democracies. One approach to mitigating the effect of misinformation focuses on individual-level interventions, equipping policymakers and the public with essential tools to curb the spread and influence of falsehoods. Here we introduce a toolbox of individual-level interventions for reducing harm from online misinformation. Comprising an up-to-date account of interventions featured in 81 scientific papers from across the globe, the toolbox provides both a conceptual overview of nine main types of interventions, including their target, scope and examples, and a summary of the empirical evidence supporting the interventions, including the methods and experimental paradigms used to test them. The nine types of interventions covered are accuracy prompts, debunking and rebuttals, friction, inoculation, lateral reading and verification strategies, media-literacy tips, social norms, source-credibility labels, and warning and fact-checking labels.

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Fig. 1: Structure of the toolbox and map of evidence.

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Data availability

All data are available at OSF (https://osf.io/ejyh6) and in the online supplement (https://interventionstoolbox.mpib-berlin.mpg.de).

Code availability

All code is available at OSF (https://osf.io/ejyh6).

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Acknowledgements

We thank S. Vrtovec, F. Stock and A. Horsley for research assistance and D. Ain for editing the manuscript and the online appendix. We also thank J. van Bavel, W. Brady, Z. Epstein, M. Leiser, L. Oswald, J. Rozenbeek and A. Simchon for their contributions during the workshop ‘Behavioral interventions for promoting truth and democratic discourse in online environments’. The study was funded by a grant from the Volkswagen Foundation to R.H., S.L. and S.M.H. (project ‘Reclaiming individual autonomy and democratic discourse online: how to rebalance human and algorithmic decision making’). A.K., P.L.-S., R.H., S.L. and S.M.H. also acknowledge funding from the EU Horizon project no. 101094752 ‘Social media for democracy (SoMe4Dem)’. S.L. was supported by a Research Award from the Humboldt Foundation in Germany and by an ERC Advanced Grant (no. 101020961 PRODEMINFO) while this research was conducted. U.K.H.E. was supported by an Australian Research Council Future Fellowship (no. FT190100708). H.L. acknowledges funding from the French Agence Nationale de la Recherche under the Investissement d'Avenir program ANR-17-EURE-0010.

Author information

Author notes

  1. These authors jointly supervised this work: Anastasia Kozyreva, Philipp Lorenz-Spreen, Stefan M. Herzog, Ullrich K. H. Ecker, Stephan Lewandowsky, Ralph Hertwig.

Authors and Affiliations

  1. Center for Adaptive Rationality, Max Planck Institute for Human Development, Berlin, Germany

    Anastasia Kozyreva, Philipp Lorenz-Spreen, Stefan M. Herzog, Ralph Hertwig & Michael Geers

  2. School of Psychological Science & Public Policy Institute, University of Western Australia, Perth, Western Australia, Australia

    Ullrich K. H. Ecker

  3. School of Psychological Science, University of Bristol, Bristol, UK

    Stephan Lewandowsky

  4. Department of Psychology, University of Potsdam, Potsdam, Germany

    Stephan Lewandowsky

  5. Department of Economics, Lahore University of Management Sciences, Lahore, Pakistan

    Ayesha Ali

  6. Craig Newmark Center, School of Journalism, Columbia University, New York, NY, USA

    Joe Bak-Coleman

  7. Department of Learning and Instructional Sciences, University of Haifa, Haifa, Israel

    Sarit Barzilai

  8. Department of Psychology, University of Cambridge, Cambridge, UK

    Melisa Basol & Sander van der Linden

  9. Department of Political Science, Massachusetts Institute of Technology, Cambridge, MA, USA

    Adam J. Berinsky

  10. Institute for Planetary Health Behaviour, University of Erfurt, Erfurt, Germany

    Cornelia Betsch & Philipp Schmid

  11. Bernhard Nocht Institute for Tropical Medicine, Hamburg, Germany

    Cornelia Betsch & Philipp Schmid

  12. Melbourne Centre for Behaviour Change, University of Melbourne, Melbourne, Victoria, Australia

    John Cook

  13. Department of Psychology and Human Development, Vanderbilt University, Nashville, TN, USA

    Lisa K. Fazio

  14. Department of Psychology, Humboldt University of Berlin, Berlin, Germany

    Michael Geers

  15. Department of Politics and School of Public and International Affairs, Princeton University, Princeton, NJ, USA

    Andrew M. Guess

  16. Department of Political Science, Ohio State University, Columbus, OH, USA

    Haifeng Huang

  17. Departments of Economics and Political Science, Instituto Tecnológico Autónomo de México, Mexico City, Mexico

    Horacio Larreguy

  18. Department of Experimental Psychology, University of Oxford, Oxford, UK

    Rakoen Maertens

  19. IMT School for Advanced Studies Lucca, Lucca, Italy

    Folco Panizza

  20. Department of Psychology, Cornell University, Ithaca, NY, USA

    Gordon Pennycook

  21. Department of Psychology, University of Regina, Regina, Saskatchewan, Canada

    Gordon Pennycook

  22. Sloan School of Management, Massachusetts Institute of Technology, Cambridge, MA, USA

    David G. Rand

  23. Department of Psychology, New York University, New York, NY, USA

    Steve Rathje

  24. Department of Politics, University of Exeter, Exeter, UK

    Jason Reifler & Paula Szewach

  25. Centre for Language Studies, Radboud University Nijmegen, Nijmegen, the Netherlands

    Philipp Schmid

  26. Graduate School of Education, Stanford University, Stanford, CA, USA

    Mark Smith & Sam Wineburg

  27. Department of Political Science, Northeastern University, Boston, MA, USA

    Briony Swire-Thompson

  28. Barcelona Supercomputing Center, Barcelona, Spain

    Paula Szewach

Authors
  1. Anastasia Kozyreva
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  2. Philipp Lorenz-Spreen
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  3. Stefan M. Herzog
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  4. Ullrich K. H. Ecker
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  5. Stephan Lewandowsky
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  6. Ralph Hertwig
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  7. Ayesha Ali
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  8. Joe Bak-Coleman
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  9. Sarit Barzilai
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  10. Melisa Basol
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  11. Adam J. Berinsky
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  12. Cornelia Betsch
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  13. John Cook
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  14. Lisa K. Fazio
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  15. Michael Geers
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  16. Andrew M. Guess
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  20. Folco Panizza
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  21. Gordon Pennycook
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  28. Paula Szewach
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  29. Sander van der Linden
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  30. Sam Wineburg
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Contributions

Conceptualization: A.K., P.L.-S., S.M.H., S.L., U.K.H.E. and R.H. Visualization: A.K. and S.M.H. Supervision: P.L.-S., S.M.H., S.L., U.K.H.E. and R.H. Writing—original draft: A.K., P.L.-S., U.K.H.E., M.G. and J.B.-C. Writing—review and editing: A.K., P.L.-S., S.M.H., S.L., U.K.H.E. and R.H. Coordinating authors: A.K., P.L.-S., S.M.H., S.L., U.K.H.E. and R.H. Contributing authors: A.A., J.B.-C., S.B., M.B., A.J.B., C.B., J.C., L.K.F., M.G., A.M.G., H.H., H.L., R.M., F.P., G.P., D.G.R., S.R., J.R., P. Schmid, M.S., B.S.-T., P. Szewach, S.v.d.L. and S.W.

Corresponding author

Correspondence to Anastasia Kozyreva.

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Competing interests

For studies included in the evidence overview, G.P., D.G.R. and A.J.B. received research funding and research support through gifts from Google and Meta. A.M.G. and A.A. received an unrestricted research grant from Meta. L.K.F. received research funding from Meta. S.v.d.L., S.R. and S.L. received research funding from Google Jigsaw. S.W. and M.S. received research funding from Google.org. All other authors declare no competing interests.

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Kozyreva, A., Lorenz-Spreen, P., Herzog, S.M. et al. Toolbox of individual-level interventions against online misinformation. Nat Hum Behav (2024). https://doi.org/10.1038/s41562-024-01881-0

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