Examining the Role of Distrust in Science and Social Media Use: Effects on Susceptibility to COVID Misperceptions with Panel Data

References

• Agley, J. (2020). Assessing changes in US public trust in science amid the COVID-19 pandemic. Public Health, 183, 122–125. https://doi.org/10.1016/j.puhe.2020.05.004
   PubMed Web of Science ®Google Scholar
• American Journal of Managed Care. (2021, January, 1). A timeline of COVID-19 developments in 2020. AJMC. https://www.ajmc.com/view/a-timeline-of-covid19-developments-in-2020
   Google Scholar
• Basch, C. H., Meleo-Erwin, Z., Fera, J., Jaime, C., & Basch, C. E. (2021). A global pandemic in the time of viral memes: COVID-19 vaccine misinformation and disinformation on TikTok. Human Vaccines & Immunotherapeutics, 17(8), 2373–2377. https://doi.org/10.1080/21645515.2021.1894896
   PubMed Web of Science ®Google Scholar
• Blumler, J. G., & Katz, E. (1974). The uses of mass communications. Sage.
   Google Scholar
• Boyle, P. (2022, May 4). Why do so many Americans distrust science? AAMCNEWS. https://www.aamc.org/news-insights/why-do-so-many-americans-distrust-science
   Google Scholar
• Brossard, D. (2013). New media landscapes and the science information consumer. Proceedings of the National Academy of Sciences, 110(supplement_3), 14096–14101.
   PubMedGoogle Scholar
• Calvillo, D. P., Ross, B. J., Garcia, R. J., Smelter, T. J., & Rutchick, A. M. (2020). Political ideology predicts perceptions of the threat of COVID-19 (And susceptibility to fake news about it). Social Psychological and Personality Science, 11(8), 1119–1128. https://doi.org/10.1177/1948550620940539
   Web of Science ®Google Scholar
• Cardenas, N. C. (2022). ‘Europe and United States vaccine hesitancy’: Leveraging strategic policy for ‘Infodemic’on COVID-19 vaccines. Journal of Public Health, 44(2), e315–e316. https://doi.org/10.1093/pubmed/fdab228
   PubMed Web of Science ®Google Scholar
• Chou, W. Y. S., Gaysynsky, A., & Cappella, J. N. (2020). Where we go from here: Health misinformation on social media. American Journal of Public Health, 110(S3), S273–S275. https://doi.org/10.2105/AJPH.2020.305905
   PubMedGoogle Scholar
• Chung, M. (2017). Not just numbers: The role of social media metrics in online news evaluations. Computers in Human Behavior, 75, 949–957. https://doi.org/10.1016/j.chb.2017.06.022
   Web of Science ®Google Scholar
• Cinelli, M., Quattrociocchi, W., Galeazzi, A., Valensise, C. M., Brugnoli, E., Schmidt, A. L., & Scala, A. (2020). The COVID-19 social media infodemic. Scientific Reports, 10(1), 1–10. https://doi.org/10.1038/s41598-020-73510-5
   PubMed Web of Science ®Google Scholar
• Del Corona, L. (2021). Distrust in science as a threat to scientific freedom. Some considerations in light of COVID-19 emergency. CERIDAP, 2021(2), 1–14.
   Google Scholar
• Diehl, T., Huber, B., Gil de Zúñiga, H., & Liu, J. (2021). Social media and beliefs about climate change: A cross-national analysis of news use, political ideology, and trust in science. International Journal of Public Opinion Research, 33(2), 197–213. https://doi.org/10.1093/ijpor/edz040
   Web of Science ®Google Scholar
• Diehl, T., & Lee, S. (2022). Testing the cognitive involvement hypothesis on social media: ‘News finds me’ perceptions, partisanship, and fake news credibility. Computers in Human Behavior. Advance online publication. https://doi.org/10.1016/j.chb.2021.107121
   Web of Science ®Google Scholar
• Eichengreen, B., Aksoy, C. G., & Saka, O. (2021). Revenge of the experts: Will COVID-19 renew or diminish public trust in science? Journal of Public Economics, 193, 104343. https://doi.org/10.1016/j.jpubeco.2020.104343
   PubMed Web of Science ®Google Scholar
• Evanega, S., Lynas, M., Adams, J., Smolenyak, K., & Insights, C. G. (2020). Coronavirus misinformation: Quantifying sources and themes in the COVID-19 “infodemic”. JMIR Preprints. https://doi.org/10.2196/preprints.25143
   Google Scholar
• Eveland, W. P., Jr., Hayes, A. F., Shah, D. V., & Kwak, N. (2005). Understanding the relationship between communication and political knowledge: A model comparison approach using panel data. Political Communication, 22(4), 423–446. https://doi.org/10.1080/10584600500311345
   Web of Science ®Google Scholar
• Farr, C. (2020, May 23). Why scientists are changing their minds and disagreeing during the coronavirus pandemic. CNBC. https://www.cnbc.com/2020/05/23/why-scientists-change-their-mind-and-disagree.html
   Google Scholar
• Feinstein, N. (2011). Salvaging science literacy. Science Education, 95(1), 168–185. https://doi.org/10.1002/sce.20414
   Web of Science ®Google Scholar
• Ferrara, E., Cresci, S., & Luceri, L. (2020). Misinformation, manipulation, and abuse on social media in the era of COVID-19. Journal of Computational Social Science, 3(2), 271–277. https://doi.org/10.1007/s42001-020-00094-5
   PubMedGoogle Scholar
• Ferre-Sandurni, L., & McKinley, J. (2020, March 13). Alex Jones is told to stop selling sham anti-coronavirus toothpaste. The New York Times. https://www.nytimes.com/2020/03/13/nyregion/alex-jones-coronavirus-cure.html
   Google Scholar
• Freiling, I., Krause, N. M., Scheufele, D. A., & Brossard, D. (2021). Believing and sharing misinformation, fact-checks, and accurate information on social media: The role of anxiety during COVID-19. New Media & Society, 25(1), 141–162. https://doi.org/10.1177/14614448211011451
   Web of Science ®Google Scholar
• Gallup. (2021). Americans’ trust in media dips to second lowest on record. https://news.gallup.com/poll/355526/americans-trust-media-dips-second-lowest-record.aspx
   Google Scholar
• Goyanes, M., Ardèvol-Abreu, A., & Gil de Zúñiga, H. (2021). Antecedents of news avoidance: Competing effects of political interest, news overload, trust in news media, and “news finds me” perception. Digital Journalism, 11(1), 1–18. https://doi.org/10.1080/21670811.2021.1990097
   Web of Science ®Google Scholar
• Hameleers, M., Reinemann, C., Schmuck, D., & Fawzi, N. (2019). The persuasiveness of populist communication: Conceptualizing the effects and political consequences of populist communication from a social identity perspective. In C. Reinemann, J. Stanyer, T. Aalberg, F. Esser, & C. H. de Vreese (Eds.), Communicating populism: Comparing actor perceptions, media coverage, and effects on citizens in Europe (pp. 143–167). Routledge.
   Google Scholar
• Hameleers, M., & Van der Meer, T. G. (2020). Misinformation and polarization in a high-choice media environment: How effective are political fact-checkers? Communication Research, 47(2), 227–250. https://doi.org/10.1177/0093650218819671
   Web of Science ®Google Scholar
• Hara, N., & Sanfilippo, M. R. (2016). Co-constructing controversy: Content analysis of collaborative knowledge negotiation in online communities. Information, Communication & Society, 19(11), 1587–1604. https://doi.org/10.1080/1369118X.2016.1142595
   Web of Science ®Google Scholar
• Hart, P. S., Chinn, S., & Soroka, S. (2020). Politicization and polarization in COVID-19 news coverage. Science Communication, 42(5), 679–697. https://doi.org/10.1177/1075547020950735
   PubMed Web of Science ®Google Scholar
• Havey, N. F. (2020). Partisan public health: How does political ideology influence support for COVID-19 related misinformation? Journal of Computational Social Science, 3(2), 319–342. https://doi.org/10.1007/s42001-020-00089-2
   PubMedGoogle Scholar
• Hendriks, F., Kienhues, D., Bromme, R., & Wicherts, J. M. (2015). Measuring laypeople’s trust in experts in a digital age: The Muenster Epistemic Trustworthiness Inventory (METI). PloS One, 10(10), e0139309. https://doi.org/10.1371/journal.pone.0139309
   PubMed Web of Science ®Google Scholar
• Hu, L. T., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling, 6(1), 1–55. https://doi.org/10.1080/10705519909540118
   Web of Science ®Google Scholar
• Hutchens, M. J., Hmielowski, J. D., Beam, M. A., & Romanova, E. (2021). Trust over use: Examining the roles of media use and media trust on misperceptions in the 2016 US presidential election. Mass Communication and Society, 24(5), 701–724. https://doi.org/10.1080/15205436.2021.1904262
   Web of Science ®Google Scholar
• Jang, S. M., Mckeever, B. W., Mckeever, R., & Kim, J. K. (2019). From social media to mainstream news: The information flow of the vaccine-autism controversy in the US, Canada, and the UK. Health Communication, 34(1), 110–117. https://doi.org/10.1080/10410236.2017.1384433
   PubMed Web of Science ®Google Scholar
• Jones-Jang, S. M., & Chung, M. (2022). Can we blame social media for polarization? Counter-evidence against filter bubble claims during the COVID-19 pandemic. New Media and Society, 146144482210995. Advance online publication. https://doi.org/10.1177/14614448221099591
   Web of Science ®Google Scholar
• Kelner, M. (2022). Robert F Kennedy Jr: America’s most famous political dynasty has given rise to one of its leading COVID anti-vaxxers - and his message reaches millions. Sky news. https://news.sky.com/story/robert-f-kennedy-jr-americas-most-famous-political-dynasty-has-given-rise-to-one-of-its-leading-covid-anti-vaxxers-and-his-falsehoods-reach-millions-12528811
   Google Scholar
• Kim, Y., Chen, H. T., & Gil de Zúñiga, H. G. (2013). Stumbling upon news on the internet: Effects of incidental news exposure and relative entertainment use on political engagement. Computers in Human Behavior, 29(6), 2607–2614. https://doi.org/10.1016/j.chb.2013.06.005
   Web of Science ®Google Scholar
• Kreps, S. E., & Kriner, D. L. (2020). Model uncertainty, political contestation, and public trust in science: Evidence from the COVID-19 pandemic. Science Advances, 6(43), eabd4563. https://doi.org/10.1126/sciadv.abd4563
   PubMed Web of Science ®Google Scholar
• La Bella, E., Allen, C., & Lirussi, F. (2021). Communication vs evidence: What hinders the outreach of science during an infodemic? A narrative review. Integrative Medicine Research, 10(4), 100731. https://doi.org/10.1016/j.imr.2021.100731
   PubMed Web of Science ®Google Scholar
• Lee, S. Y., & Hawkins, R. P. (2016). Worry as an uncertainty-associated emotion: Exploring the role of worry in health information seeking. Health Communication, 31(8), 926–933. https://doi.org/10.1080/10410236.2015.1018701
   PubMed Web of Science ®Google Scholar
• Lee, S., & Jones-Jang, S. M. (2022). Cynical nonpartisans: The role of misinformation in political cynicism during the 2020 US presidential election. New Media & Society. Advance online publication. https://doi.org/10.1177/14614448221116036
   Web of Science ®Google Scholar
• Lee, H., & Oh, H. J. (2017). Normative mechanism of rumor dissemination on Twitter. Cyberpsychology, Behavior, and Social Networking, 20(3), 164–171. https://doi.org/10.1089/cyber.2016.0447
   PubMed Web of Science ®Google Scholar
• Lee, E. J., & Tandoc, E. C., Jr. (2017). When news meets the audience: How audience feedback online affects news production and consumption. Human Communication Research, 43(4), 436–449. https://doi.org/10.1111/hcre.12123
   Web of Science ®Google Scholar
• Lee, S., Tandoc Jr, E. C., Jr., & Diehl, T. (2023). Uninformed and misinformed: Advancing a theoretical model for social media news use and political knowledge. Digital Journalism, 1–20. https://doi.org/10.1080/21670811.2023.2180404
   Web of Science ®Google Scholar
• Lee, S., Tandoc, E. C., Jr., & Lee, E. W. (2023). Social media may hinder learning about science; social media’s role in learning about COVID-19. Computers in Human Behavior, 138, 107487. https://doi.org/10.1016/j.chb.2022.107487
   PubMed Web of Science ®Google Scholar
• Lee, S., Yamamoto, M., & Tandoc, E. C., Jr. (2022). Why people who know less think they know about COVID-19: Evidence from US and Singapore. Journalism & Mass Communication Quarterly, 99(1), 44–68. https://doi.org/10.1177/10776990211049460
   Web of Science ®Google Scholar
• McLamore, Q., Syropoulos, S., Leidner, B., Hirschberger, G., Young, K., Zein, R. A., Baumert, A., Bilewicz, M., Bilgen, A., van Bezouw, M. J., Chatard, A., Chekroun, P., Chinchilla, J., Choi, H. S., Euh, H., Gomez, A., Kardos, P., Khoo, Y. H., Li, M., … Burrows, B. (2022). Trust in scientific information mediates associations between conservatism and coronavirus responses in the U.S., but few other nations. Scientific Reports, 12(1), 3724–3724. https://doi.org/10.1038/s41598-022-07508-6
   PubMed Web of Science ®Google Scholar
• Messing, S., & Westwood, S. J. (2014). Selective exposure in the age of social media: Endorsements trump partisan source affiliation when selecting news online. Communication Research, 41(8), 1042–1063. https://doi.org/10.1177/0093650212466406
   Web of Science ®Google Scholar
• Metag, J. (2020). What drives science media use? Predictors of media use for information about science and research in digital information environments. Public Understanding of Science, 29(6), 561–578. https://doi.org/10.1177/0963662520935062
   PubMed Web of Science ®Google Scholar
• Modgil, S., Singh, R. K., Gupta, S., & Dennehy, D. (2021). A confirmation bias view on social media induced polarisation during COVID-19. Information Systems Frontiers, 1–25. https://doi.org/10.1007/s10796-021-10222-9
   PubMed Web of Science ®Google Scholar
• Morales, G., Lee, S., Bradford, A., De Camp, A., & Tandoc, E. C., Jr. (2022). Exploring vaccine hesitancy determinants during the COVID-19 pandemic: An in-depth interview study. SSM - Qualitative Research in Health, 2, 100045. https://doi.org/10.1016/j.ssmqr.2022.100045
   PubMedGoogle Scholar
• Myrick, J. G., Nabi, R. L., & Eng, N. J. (2022). Consuming memes during the COVID pandemic: Effects of memes and meme type on COVID-related stress and coping efficacy. Psychology of Popular Media, 11(3), 316–323. https://doi.org/10.1037/ppm0000371
   Google Scholar
• Nadelson, L., Jorcyk, C., Yang, D., Jarratt Smith, M., Matson, S., Cornell, K., & Husting, V. (2014). I just don’t trust them: The development and validation of an assessment instrument to measure trust in science and scientists. School Science and Mathematics, 114(2), 76–86. https://doi.org/10.1111/ssm.12051
   Google Scholar
• Naeem, S. B., Bhatti, R., & Khan, A. (2021). An exploration of how fake news is taking over social media and putting public health at risk. Health Information & Libraries Journal, 38(2), 143–149. https://doi.org/10.1111/hir.12320
   PubMed Web of Science ®Google Scholar
• Neureiter, A., Stubenvoll, M., Kaskeleviciute, R., & Matthes, J. (2021). Trust in science, perceived media exaggeration about COVID-19, and social distancing behavior. Frontiers in Public Health, 9. https://doi.org/10.3389/fpubh.2021.670485
   PubMed Web of Science ®Google Scholar
• Pechar, E., Bernauer, T., & Mayer, F. (2018). Beyond political ideology: The impact of attitudes towards government and corporations on trust in science. Science Communication, 40(3), 291–313. https://doi.org/10.1177/1075547018763970
   Web of Science ®Google Scholar
• Pennycook, G., McPhetres, J., Zhang, Y., Lu, J. G., & Rand, D. G. (2020). Fighting COVID-19 misinformation on social media: Experimental evidence for a scalable accuracy-nudge intervention. Psychological Science, 31(7), 770–780. https://doi.org/10.1177/0956797620939054
   PubMed Web of Science ®Google Scholar
• Pew Research. (2022). Americans’ trust in scientists, other groups declines. https://www.pewresearch.org/science/2022/02/15/americans-trust-in-scientists-other-groups-declines/
   Google Scholar
• Plohl, N., & Musil, B. (2021). Modeling compliance with COVID-19 prevention guidelines: The critical role of trust in science. Psychology, Health & Medicine, 26(1), 1–12. https://doi.org/10.1080/13548506.2020.1772988
   PubMed Web of Science ®Google Scholar
• Prior, M. (2007). Post-broadcast democracy: How media choice increases inequality in political involvement and polarizes elections. Cambridge University Press.
   Google Scholar
• Ries, M. (2022). The COVID-19 infodemic: Mechanism, impact, and counter-measures—A review of reviews. Sustainability, 14(5), 2605. https://doi.org/10.3390/su14052605
   Web of Science ®Google Scholar
• Romer, D., & Jamieson, K. H. (2020). Conspiracy theories as barriers to controlling the spread of COVID-19 in the U.S. Social Science & Medicine, 263, 113356. https://doi.org/10.1016/j.socscimed.2020.113356
   PubMed Web of Science ®Google Scholar
• Rosseel, Y. (2012). Lavaan: An R package for structural equation modeling. Journal of Statistical Software, 48(2), 1–36. https://doi.org/10.18637/jss.v048.i02
   Web of Science ®Google Scholar
• Schäfer, M. S. (2016). Mediated trust in science: Concept, measurement and perspectives for the science of science communication’. Journal of Science Communication, 15(5), C02. https://doi.org/10.22323/2.15050302
   Web of Science ®Google Scholar
• Scheufele, D. A. (2013). Communicating science in social settings. Proceedings of the National Academy of Sciences, 110(supplement_3), 14040–14047.
   PubMedGoogle Scholar
• Strömbäck, J., Tsfati, Y., Boomgaarden, H., Damstra, A., Lindgren, E., Vliegenthart, R., & Lindholm, T. (2020). News media trust and its impact on media use: Toward a framework for future research. Annals of the International Communication Association, 44(2), 139–156. https://doi.org/10.1080/23808985.2020.1755338
   Google Scholar
• Su, Y. (2021). It doesn’t take a village to fall for misinformation: Social media use, discussion heterogeneity preference, worry of the virus, faith in scientists, and COVID-19-related misinformation beliefs. Telematics and Informatics. Advance online publication. https://doi.org/10.1016/j.tele.2020.101547
   PubMed Web of Science ®Google Scholar
• Van Der Bles, A. M., van der Linden, S., Freeman, A. L., & Spiegelhalter, D. J. (2020). The effects of communicating uncertainty on public trust in facts and numbers. Proceedings of the National Academy of Sciences, 117(14), 7672–7683.
   PubMed Web of Science ®Google Scholar
• Viswanath, K., Lee, E. W., & Pinnamaneni, R. (2020). We need the lens of equity in COVID-19 communication. Health Communication, 35(14), 1743–1746. https://doi.org/10.1080/10410236.2020.1837445
   PubMed Web of Science ®Google Scholar
• World Health Organization. (2020). Novel Coronavirus(2019-nCov) [situation report]. https://www.who.int/docs/default-source/coronaviruse/situation-reports/20200202-sitrep-13-ncov-v3.pdf?sfvrsn=195f4010_6
   Google Scholar