Sociologický časopis / Czech Sociological Review | DOI: 10.13060/csr.2026.021

Disinformation in Science: A Review of Empirical Evidence on Causes, Diffusion, and Countermeasures

Jakub Lysek ORCID..., Pavel Šaradín ORCID..., Markéta Zapletalová ORCID..., Tomáš Lebeda ORCID..., Eva Lebedová ORCID..., Daniela Ostrá ORCID..., Ondřej Molnár ORCID...
Filozofická fakulta, Univerzita Palackého v Olomouci

This article presents a synthesis of empirical quantitative findings on the individual-level factors that influence the susceptibility to believe scientific and technological disinformation and the willingness to disseminate it. The review identifies determinants divided into three main categories: socioeconomic status (SES), attitudinal and value orientations, and psychological factors. Key findings indicate that the influence of formal education and economic capital is often moderated, or even overshadowed, by ideological orientation and deeper personality and psychological traits. The intentional dissemination of disinformation is strongly associated with two factors in particular that are part of psychology’s Dark Triad theory: narcissism and Machiavellianism. Conversely, cognitive reflection (CRT) emerges as the strongest protective factor. Consequently, effective defence strategies must move away from simplistic fact-checking and focus on developing psychological resilience, metacognition, and critical thinking in recipients. Future research should shift from predominantly focusing on respondents via additive regression modelling towards investigating interaction and moderation effects and thematically towards examining the role of political and business elites as drivers of disinformation narratives.

Keywords: disinformation, review study, individual factors, SES, cognitive reflection, psychological factors

Received: January 28, 2026; Revised: May 28, 2026; Accepted: June 4, 2026; Prepublished online: June 12, 2026 

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    References

    1. Agley, J. a Xiao, Y. (2021). Misinformation about COVID-19: Evidence for differential latent profiles and a strong association with trust in science. BMC Public Health, 21, 89. https://doi.org/10.1186/s12889-020-10103-x Go to original source...
    2. Ahadzadeh, A. S., Ong, F. S. a Wu, S. L. (2023). Social media skepticism and belief in conspiracy theories about COVID-19: The moderating role of the dark triad. Current Psychology, 42, 8874-8886. https://doi.org/10.1007/s12144-021-02198-1 Go to original source...
    3. Ahmed, S. a Masood, M. (2025). Dark personalities in the digital arena: How psychopathy and narcissism shape online political participation. Humanities and Social Sciences Communications, 12(1), 1-11. https://doi.org/10.1057/s41599-025-05195-y Go to original source...
    4. Ahmed, S. a Rasul, M. E. (2023). Examining the association between social media fatigue, cognitive ability, narcissism and misinformation sharing: Cross-national evidence from eight countries. Scientific Reports, 13(1), 15416. https://doi.org/10.1038/s41598-023-42614-z Go to original source...
    5. Arroyo-Barrigüete, J. L., Bellón Núñez-Mera, C., Labrador Fernández, J. a De Nicolas, V. L. (2023). Dunning-Kruger effect and flat-earthers: An exploratory analysis. Public Understanding of Science, 32(7), 835-844. https://doi.org/10.1177/09636625231166255 Go to original source...
    6. Auchynnikava, A. a Habibov, N. (2024). Is the effect of educational attainments on trust in scientists underestimated? Science & Education, 3. https://doi.org/10.1007/s11191-024-00551-x Go to original source...
    7. Buchanan, T. a Benson, V. (2019). Spreading disinformation on Facebook: Do trust in message source, risk propensity, or personality affect the organic reach of 'fake news'? Social media+ society, 5(4), (online). https://doi.org/10.1177/2056305119888654 Go to original source...
    8. Buchanan, T. (2025). Trust, personality, and belief as determinants of the organic reach of political disinformation on social media. The Social Science Journal, 62(3), 633-644. https://doi.org/10.1080/03623319.2021.1975085 Go to original source...
    9. Calvillo, D. P., Garcia, R. J., Bertrand, K. a Mayers, T. A. (2021). Personality factors and self-reported political news consumption predict susceptibility to political fake news. Personality and Individual Differences, 174, 110666. https://doi.org/10.1016/j.paid.2021.110666 Go to original source...
    10. Calvillo, D. P., León, A. a Rutchick, A. M. (2024). Personality and misinformation. Current Opinion in Psychology, 55, 101752. https://doi.org/10.1016/j.copsyc.2023.101752 Go to original source...
    11. Cíbik, M. a Hardoš, P. (2022). Conspiracy theories and reasonable pluralism. European Journal of Political Theory, 21(3), 445-465. https://doi.org/10.1177/1474885119899232 Go to original source...
    12. Cichocka, A., Marchlewska, M. a Biddlestone, M. (2022). Why do narcissists find conspiracy theories so appealing? Current Opinion in Psychology, 47, 101386. https://doi.org/10.1016/j.copsyc.2022.101386 Go to original source...
    13. Cosgrove, T. J. a Murphy, C. P. (2023). Narcissistic susceptibility to conspiracy beliefs exaggerated by education, reduced by cognitive reflection. Frontiers in Psychology, 14, 1164725. https://doi.org/10.3389/fpsyg.2023.1164725 Go to original source...
    14. Costello, T. H., Bowes, S. M., Stevens, S. T., Waldman, I. D., Tasimi, A. a Lilienfeld, S. O. (2022). Clarifying the structure and nature of left-wing authoritarianism. Journal of Personality and Social Psychology, 122(1), 135. https://doi.org/10.1037/pspp0000341 Go to original source...
    15. Ditto, P. H., Liu, B. S., Clark, C. J., Wojcik, S. P., Chen, E. E., Grady, R. H., Celniker, J. B. a Zinger, J. F. (2019). At least bias is bipartisan: A meta-analytic comparison of partisan bias in liberals and conservatives. Perspectives on Psychological Science, 14(2), 273-291. https://doi.org/10.1177/1745691617746796 Go to original source...
    16. Ecker, U. K. H., Lewandowsky, S., Cook, J., Schmid, P., Fazio, L. K., Brashier, N., Kendeou, P., Vraga, E. K. a Amazeen, M. A. (2022). The psychological drivers of misinformation belief and its resistance to correction. Nature Reviews Psychology, 1(1), 13-29. https://doi.org/10.1038/s44159-021-00006-y Go to original source...
    17. Flakus, M., Koc, P., Plisiecki, H. a Pokropek, A. (2025). Behind beliefs - collective narcissism, political orientation, and belief in disinformation in the time of war in Ukraine. Social Psychology. https://doi.org/10.1027/1864-9335/a000571 Go to original source...
    18. George, J. F. (2024). Discovering why people believe disinformation about healthcare. Plos One, 19(3), e0300497. https://doi.org/10.1371/journal.pone.0300497 Go to original source...
    19. Gioia, F., Imperato, C., Boursier, V., Franceschini, C., Schimmenti, A. a Musetti, A. (2023). The role of defense styles and psychopathological symptoms on adherence to conspiracy theories during the COVID-19 pandemic. Scientific Reports, 13, 3482. https://doi.org/10.1038/s41598-023-30531-0 Go to original source...
    20. Gordon, D. S. a Birney, M. E. (2025). Spite and science-denial: Exploring the role of spitefulness in conspiracy ideation and COVID-19 conspiracy beliefs. Journal of Social Issues, 81: e12662. https://doi.org/10.1111/josi.12662 Go to original source...
    21. Gundersen, A. B., van der Linden, S., Piasecki, J., Ryguła, R., Noworyta, K. a Kunst, J. R. (2024). Predicting misinformation beliefs across four countries: The role of narcissism, conspiracy mentality, social trust, and perceptions of unsafe neighborhoods. Journal of Social and Political Psychology, 12(2), 265-283. https://doi.org/10.5964/jspp.13385 Go to original source...
    22. Gruener, S. (2024). Determinants of gullibility to misinformation: A study of climate change, COVID-19 and artificial intelligence. Journal of Interdisciplinary Economics, 36(1), 58-78. https://doi.org/10.1177/02601079221083482 Go to original source...
    23. Harris, E. A., DeMora, S. L. a Albarracín, D. (2024). The consequences of misinformation concern on media consumption. Harvard Kennedy School Misinformation Review, 5(3). https://doi.org/10.37016/mr-2020-149 Go to original source...
    24. Haupt, M. R., Cuomo, R., Mackey, T. K. a Coulson, S. (2024). The role of narcissism and motivated reasoning on misinformation propagation. Frontiers in Communication, 9, 1472631. https://doi.org/10.3389/fcomm.2024.1472631 Go to original source...
    25. Hayes, A. F. (2017). Introduction to mediation, moderation, and conditional process analysis: A regression-based approach. Guilford Publications.
    26. Humprecht, E., Esser, F. a Van Aelst, P. (2020). Resilience to online disinformation: A framework for cross-national comparative research. The International Journal of Press/Politics, 25(3), 493-516. https://doi.org/10.1177/1940161219900126 Go to original source...
    27. Johnson, H. (2020). Adorno and climate science denial: Lies that sound like truth. Philosophy and Social Criticism, 47(7), 831-849. https://doi.org/10.1177/0191453720975459 Go to original source...
    28. Jylhä, K. M., Stanley, S. K., Ojala, M. a Clarke, E. J. R. (2023). Science denial: A narrative review and recommendations for future research and practice. European Psychologist, 28(3), 151-161. https://doi.org/10.1027/1016-9040/a000487 Go to original source...
    29. Kahneman, D. (2012). Myšlení: rychlé a pomalé. Jan Melvil.
    30. Kamalrathne, T., Jayasekara, J. R., Amaratunga, D., Haigh, R., Kodituwakku, L. a Rupasinghe, C. (2024). Panic in the pandemic: Determinants of vaccine hesitancy and the dilemma of public health information sharing during the COVID-19 pandemic in Sri Lanka. International Journal of Environmental Research and Public Health, 21(1268). https://doi.org/10.3390/ijerph21101268 Go to original source...
    31. Koblížek, T., Hanych, M. a Kalenský, J. (2025). Dezinformace a hate speech: Z hlediska filozofie, práva a bezpečnosti. Academia.
    32. Kouba, K. a Lysek, J. (2019). What affects invalid voting? A review and meta-analysis. Government and Opposition, 54(4), 745-775. https://doi.org/10.1017/gov.2018.33 Go to original source...
    33. Kuo, H.-Y. a Chen, S.-Y. (2025). Predicting user engagement in health misinformation correction on social media platforms in Taiwan: Content analysis and text mining study. Journal of Medical Internet Research, 27, e65631. https://doi.org/10.2196/65631 Go to original source...
    34. Lai, K., Jing, G., Zhao, J. a Xiong, X. (2024). How dark triad influences rumors spreading on social media? Mediating role of declining third-person effect. Current Psychology, 43(8), 7007-7013. https://doi.org/10.1007/s12144-023-04903-8 Go to original source...
    35. Lewandowsky, S. (2021). Liberty and the pursuit of science denial. Current Opinion in Behavioral Sciences, 42, 65-69. https://doi.org/10.1016/j.cobeha.2021.02.024 Go to original source...
    36. Li, J. a Chang, X. (2023). Combating misinformation by sharing the truth: a study on the spread of fact-checks on social media. Information Systems Frontiers, 25(4), 1479-1493. https://doi.org/10.1007/s10796-022-10296-z Go to original source...
    37. Loomba, S., de Figueiredo, A., Piatek, S. J., de Graaf, K. a Larson, H. J. (2021). Measuring the impact of COVID-19 vaccine misinformation on vaccination intent in the UK and USA. Nature Human Behaviour, 5(3), 337-348. https://doi.org/10.1038/s41562-021-01056-1 Go to original source...
    38. Lyu, H., Zheng, Z. a Luo, J. (2021). Misinformation versus facts: Understanding the influence of news regarding COVID-19 vaccines on vaccine uptake. arXiv preprint arXiv:2106.07435v2. https://doi.org/10.34133/2022/9858292 Go to original source...
    39. Ndasauka, Y., Twabi, H. S., Kainja, J., Gunde, A. M. a Makhumula Mtimuni, C. (2024). Knowledge, attitudes and demographic drivers for COVID 19 vaccine hesitancy in Malawi. Scientific Reports, 14, 9578. https://doi.org/10.1038/s41598-024-60042-5 Go to original source...
    40. Normandin, A. C. (2022). Redefining 'misinformation,' 'disinformation,' and 'fake news': Using social science research to form an interdisciplinary model of online limited forums on social media platforms. Campbell Law Review, 44(2), 289-334.
    41. Nyhan, B., Reifler, J. (2010). When corrections fail: The persistence of political misperceptions. Political Behavior, 32, 303-330. https://doi.org/10.1007/s11109-010-9112-2 Go to original source...
    42. Osatuyi, B. a Dennis, A. R. (2025). The role of personality in fake news sharing on social media: Reducing extraverts' proclivity to share fake news. Information Systems Frontiers, 1-20. https://doi.org/10.1007/s10796-025-10613-2 Go to original source...
    43. Ozimek, P., Nettersheim, M., Rohmann, E. a Bierhoff, H.-W. (2022). Science vs. conspiracy theory about COVID-19: Need for cognition and openness to experience increased belief in conspiracy-theoretical postings on social media. Behavioral Sciences, 12(11), 435. https://doi.org/10.3390/bs12110435 Go to original source...
    44. Pavliuc, A., George, A., Spezzano, F., Giachanou, A., Spaiser, V. a Bright, J. (2023). Editorial: Multidisciplinary approaches to mis- and disinformation studies. Social Media + Society, 9(1). https://doi.org/10.1177/20563051221150405 Go to original source...
    45. Pierri, F., Perry, B., DeVerna, M. R., Yang, K.-C., Axelrod, D., Bryden, J. a Menczer, F. (2021). Online misinformation is linked to early COVID-19 vaccination hesitancy and refusal. Scientific Reports, 11(1), 6201. https://doi.org/10.2196/preprints.32237 Go to original source...
    46. Peter, E. L., Kwantes, P. J., D'Agata, M. T. a Vallikanthan, J. (2024). The role of personality traits and online behavior in belief in fake news. Humanities and Social Sciences Communications, 11(1), 1-10. https://doi.org/10.1057/s41599-024-03573-6 Go to original source...
    47. Posetti, J. a Matthews, A. (2018). A short guide to the history of 'fake news' and disinformation. International Center for Journalists.
    48. Realfonzo, U. A. (2026, 14. ledna). US tech giants allying with European far-right to strip back EU rules. The Brussels Times. https://www.brusselstimes.com/1916422/us-tech-giants-allying-with-european-far-right-to-strip-back-eu-rules
    49. Roschke, K., Koskan, A. M., Sivanandam, S. a Irby, J. (2024). Partisan media, trust, and media literacy: Regression analysis of predictors of COVID-19 knowledge. JMIR Formative Research, 8, e53904. https://doi.org/10.2196/53904 Go to original source...
    50. Rothbart, D. a Bere, M. (2024). Political narcissism of right-wing extremists: Understanding aggression of the proud boys. Peace and Conflict: Journal of Peace Psychology, 30(4), 540-552. https://doi.org/10.1037/pac0000759 Go to original source...
    51. Rutjens, B. T. a Većkalov, B. (2022). Conspiracy beliefs and science rejection. Current Opinion in Psychology, 46, 101392. https://doi.org/10.1016/j.copsyc.2022.101392 Go to original source...
    52. Singh, K., Lima, G., Cha, M., Cha, C., Kulshrestha, J., Ahn, Y.-Y. a Varol, O. (2022). Misinformation, believability, and vaccine acceptance over 40 countries: Takeaways from the initial phase of the COVID-19 infodemic. PLOS ONE, 17(2), e0263381. https://doi.org/10.1371/journal.pone.0263381 Go to original source...
    53. Smets, K. a Van Ham, C. (2013). The embarrassment of riches? A meta-analysis of individual-level research on voter turnout. Electoral Studies, 32(2), 344-359. https://doi.org/10.1016/j.electstud.2012.12.006 Go to original source...
    54. Southwell, B. G., Brennen, J. S. B., Paquin, R., Boudewyns, V. a Zeng, J. (2022). Defining and measuring scientific misinformation. Annals of the American Academy of Political and Social Science, 700(1), 98-111. https://doi.org/10.1177/00027162221084709 Go to original source...
    55. Spampatti, T., Hahnel, U. J., Trutnevyte, E. a Brosch, T. (2024). Psychological inoculation strategies to fight climate disinformation across 12 countries. Nature Human Behaviour, 8(2), 380-398. https://doi.org/10.1038/s41562-023-01736-0 Go to original source...
    56. Srinivas, P. Y. K. L., Das, A. a Pulabaigari, V. (2022). Fake spreader is narcissist; real spreader is Machiavellian: Prediction of fake news diffusion using psycho-sociological facets. Expert Systems with Applications, 207, 117952. https://doi.org/10.1016/j.eswa.2022.117952 Go to original source...
    57. Stecula, D. A. a Pickup, M. (2021). How populism and conservative media fuel conspiracy beliefs about COVID-19 and what it means for COVID-19 behaviors. Research and Politics, 8(1), 1-9. https://doi.org/10.1177/2053168021993979 Go to original source...
    58. Sternisko, A., Cichocka, A., Cislak, A. a Van Bavel, J. J. (2023). National narcissism predicts the belief in and the dissemination of conspiracy theories during the COVID-19 pandemic: Evidence from 56 countries. Personality and Social Psychology Bulletin, 49(1), 48-65. https://doi.org/10.1177/01461672211054947 Go to original source...
    59. Stockemer, D. a Bordeleau, J.-N. (2024). Understanding climate change conspiracy beliefs: A comparative outlook. Harvard Kennedy School (HKS) Misinformation Review, 5(6). https://doi.org/10.37016/mr-2020-162 Go to original source...
    60. Suk, J., Lukito, J., Su, M. H., Jung Kim, S., Tong, C., Sun, Z. a Sarma, P. (2022). Do I sound American? How message attributes of Internet Research Agency (IRA) disinformation relate to Twitter engagement. Computational Communication Research, 4(2), 590-628. https://doi.org/10.5117/CCR2022.2.008.SUK Go to original source...
    61. Sun, Y., a Xie, J. (2024). Who shares misinformation on social media? A meta-analysis of individual traits related to misinformation sharing. Computers in Human Behavior, 158, 108271. https://doi.org/10.1016/j.chb.2024.108271 Go to original source...
    62. Taddicken, M. a Wolff, L. (2020). 'Fake news' in science communication: Emotions and strategies of coping with dissonance online. Media and Communication, 8(1), 206-217. https://doi.org/10.17645/mac.v8i1.2495 Go to original source...
    63. Taurino, A., Colucci, M. H., Bottalico, M., Franco, T. P., Volpe, G., Violante, M., Grattagliano, I. a Laera, D. (2023). To believe or not to believe: Personality, cognitive, and emotional factors involving fake news perceived accuracy. Applied Cognitive Psychology, 37(6), 1444-1454. https://doi.org/10.1002/acp.4136 Go to original source...
    64. Tripodi, F. B., Garcia, L. C. a Marwick, A. E. (2024). 'Do your own research': Affordance activation and disinformation spread. Information, Communication & Society, 27(6), 1212-1228. https://doi.org/10.1080/1369118X.2023.2245869 Go to original source...
    65. Uscinski, J. E., Enders, A. M., Klofstad, C., Seelig, M., Funchion, J., Everett, C., Wuchty, S., Premaratne, K. a Murthi, M. (2020). Why do people believe COVID-19 conspiracy theories? Harvard Kennedy School Misinformation Review. https://doi.org/10.37016/mr-2020-015 Go to original source...
    66. Walker, B. a Vegter, A. (2023). Christ, country, and conspiracies? Christian nationalism, biblical literalism, and belief in conspiracy theories. Journal for the Scientific Study of Religion, 62(2), 278-292. https://doi.org/10.1111/jssr.12836 Go to original source...
    67. Wallace, E. a Buil, I. (2025). Individual differences in perceiving disinformation sharing as opinion leadership: Effects of dark triad traits, need for uniqueness, and green identity. Personality and Individual Differences, 238, 113105. https://doi.org/10.1016/j.paid.2025.113105 Go to original source...
    68. Wang, X., Chen, S., Yang, Y. a Dong, D. (2023). Characterizing users' propensity to misinformation engagement during COVID-19 based on the five factor model of personality. In International Conference on Human-Computer Interaction (s. 403-422). Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-35927-9_28 Go to original source...
    69. Wang, Y., McKee, M., Torbica, A. a Stuckler, D. (2019). Systematic literature review on the spread of health-related misinformation on social media. Social Science & Medicine, 240, 112552. https://doi.org/10.1016/j.socscimed.2019.112552 Go to original source...
    70. Wardle, C. a Derakhshan, H. (2017). Information disorder: Toward an interdisciplinary framework for research and policymaking (vol. 27, s. 1-107). Council of Europe.
    71. Williams, J. A., Aleroud, A. a Zimmerman, D. (2023). Detecting science-based health disinformation: a stylometric machine learning approach. Journal of Computational Social Science, 6(2), 817-843. https://doi.org/10.1007/s42001-023-00213-y Go to original source...
    72. Winter, K., Hornsey, M. J., Pummerer, L. a Sassenberg, K. (2024). Public agreement with misinformation about wind farms. Nature Communications, 15, 8888. https://doi.org/10.1038/s41467-024-53278-2 Go to original source...
    73. Xiao, X. a Su, Y. (2023). Stumble on information or misinformation? Examining the interplay of incidental news exposure, narcissism, and new media literacy in misinformation engagement. Internet Research, 33(3), 1228-1248. https://doi.org/10.1108/INTR-10-2021-0791 Go to original source...

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