The challenge of debunking health misinformation in dynamic social media conversations: online randomized study of public masking during COVID-19
Open accessPublished version of a preprint
Abstract
BACKGROUND: The spread of false and misleading health information on social media can cause individual and social harm. Research on debunking has shown that properly designed corrections can mitigate the impact of misinformation, but little is known about the impact of correction in the context of prolonged social media debates. For example, when a social media user takes to Facebook to make a false claim about a health-related practice and a health expert subsequently refutes the claim, the conversation rarely ends there. Often, the social media user proceeds by rebuking the critic and doubling down on the claim. OBJECTIVE: The aim of this study was to examine the impact of such extended back and forth between false claims and debunking attempts on observers' dispositions toward behavior that science favors. We tested competing predictions about the effect of extended exposure on people's attitudes and intentions toward masking in public during the early days of the COVID-19 pandemic and explored several psychological processes potentially underlying this effect. METHODS: A total of 500 US residents took part in an online experiment in October 2020. They reported on their attitudes and intentions toward wearing masks in public. They were then randomly assigned to one of four social media exposure conditions (misinformation only vs misinformation+correction vs misinformation+correction+rebuke vs misinformation+correction+rebuke+second correction), and reported their attitudes and intentions for a second time. They also indicated whether they would consider sharing the thread if they were to see it on social media and answered questions on potential mediators and covariates. RESULTS: Exposure to misinformation had a negative impact on attitudes and intentions toward masking (β=-.35, 95% CI -.42 to -.29; P<.001). Moreover, initial debunking of a false claim generally improved attitudes and intentions toward masking (β=.35, 95% CI .16 to .54; P<.001). However, this improvement was washed out by further exposure to false claims and debunking attempts (β=-.53, 95% CI -.72 to -.34; P<.001). The latter result is partially explained by a decrease in the perceived objectivity of truth. That is, extended exposure to false claims and debunking attempts appear to weaken the belief that there is an objectively correct answer to how people ought to behave in this situation, which in turn leads to less positive reactions toward masking as the prescribed behavior. CONCLUSIONS: Health professionals and science advocates face an underappreciated challenge in attempting to debunk misinformation on social media. Although engaging in extended debates with science deniers and other purveyors of bunk appears necessary, more research is needed to address the unintended consequences of such engagement.
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
The spread of true and false news online
Vosoughi, S., Roy, D., & Aral, S. (2018) · Science · doi:10.1126/science.aap9559 · Cited by 8,847 · cited 1× · see citing works
“Yet, content disseminated through social media sites such as Facebook, Twitter, or Reddit remains largely unregulated, and is replete with false and misleading information [3-8].”
BackgroundCognitive Reflection and Decision Making
Frederick, S. (2005) · Journal of Economic Perspectives · doi:10.1257/089533005775196732 · Cited by 5,256 · see citing works
Lazer, D. M. J., Baum, M. A., Benkler, Y., Berinsky, A. J., Greenhill, K. M., Menczer, F., Metzger, M. J., Nyhan, B., Pennycook, G., Rothschild, D., et al. (2018) · Science · doi:10.1126/science.aao2998 · Cited by 4,160 · see citing works
Prolific.ac—A subject pool for online experiments
Palan, S., & Schitter, C. (2018) · Journal of Behavioral and Experimental Finance · doi:10.1016/j.jbef.2017.12.004 · Cited by 3,450 · see citing works
Beyond the Turk: Alternative platforms for crowdsourcing behavioral research
Peer, E., Brandimarte, L., Samat, S., & Acquisti, A. (2017) · Journal of Experimental Social Psychology · doi:10.1016/j.jesp.2017.01.006 · Cited by 2,957 · see citing works
Misinformation and Its Correction: Continued Influence and Successful Debiasing
Lewandowsky, S., Ecker, U. K. H., Seifert, C. M., Schwarz, N., & Cook, J. (2012) · Psychological Science in the Public Interest · doi:10.1177/1529100612451018 · Cited by 2,920 · see citing works
The COVID-19 social media infodemic
Cinelli, M., Quattrociocchi, W., Galeazzi, A., Valensise, C. M., Brugnoli, E., Schmidt, A. L., Zola, P., Zollo, F., & Scala, A. (2020) · Scientific Reports · doi:10.1038/s41598-020-73510-5 · Cited by 2,313 · see citing works
Pennycook, G., & Rand, D. G. (2019) · Cognition · doi:10.1016/j.cognition.2018.06.011 · Cited by 2,022 · see citing works
Beyond misinformation: Understanding and coping with the “post-truth” era.
Lewandowsky, S., Ecker, U. K. H., & Cook, J. (2017) · Journal of Applied Research in Memory and Cognition · doi:10.1016/j.jarmac.2017.07.008 · Cited by 1,985 · see citing works
Systematic Literature Review on the Spread of Health-related Misinformation on Social Media
Wang, Y., McKee, M., Torbica, A., & Stuckler, D. (2019) · Social Science & Medicine · doi:10.1016/j.socscimed.2019.112552 · Cited by 1,806 · see citing works
Prevalence of health misinformation on social media: systematic review
Suarez-Lledo, V., & Alvarez-Galvez, J. (2021) · Journal of Medical Internet Research · doi:10.2196/17187 · Cited by 1,564 · see citing works
Susceptibility to misinformation about COVID-19 around the world
Roozenbeek, J., Schneider, C. R., Dryhurst, S., Kerr, J., Freeman, A. L. J., Recchia, G., van der Bles, A. M., & van der Linden, S. (2020) · Royal Society Open Science · doi:10.1098/rsos.201199 · Cited by 1,447 · see citing works
Public health and online misinformation: challenges and recommendations
Swire-Thompson, B., & Lazer, D. (2020) · Annual Review of Public Health · doi:10.1146/annurev-publhealth-040119-094127 · Cited by 1,170 · see citing works
Shifting attention to accuracy can reduce misinformation online
Pennycook, G., Epstein, Z., Mosleh, M., Arechar, A. A., Eckles, D., & Rand, D. G. (2021) · Nature · doi:10.1038/s41586-021-03344-2 · Cited by 1,155 · see citing works
Weaponized health communication: Twitter bots and Russian trolls amplify the vaccine debate
Broniatowski, D. A., Jamison, A. M., Qi, S., AlKulaib, L., Chen, T., Benton, A., Quinn, S. C., & Dredze, M. (2018) · American Journal of Public Health · doi:10.2105/ajph.2018.304567 · Cited by 1,149 · see citing works
Bruder, M., Haffke, P., Neave, N., Nouripanah, N., & Imhoff, R. (2013) · Frontiers in Psychology · doi:10.3389/fpsyg.2013.00225 · Cited by 1,049 · cited 2× · see citing works
“89) rated on 7-point scales (1=strongly disagree, 7=strongly agree) adapted from Bruder et al [57].”
BackgroundSocial media and vaccine hesitancy
Wilson, S. L., & Wiysonge, C. S. (2020) · BMJ Global Health · doi:10.1136/bmjgh-2020-004206 · Cited by 978 · see citing works
Cook, J., Lewandowsky, S., & Ecker, U. K. H. (2017) · PLOS ONE · doi:10.1371/journal.pone.0175799 · Cited by 971 · see citing works
Fighting misinformation on social media using crowdsourced judgments of news source quality
Pennycook, G., & Rand, D. G. (2019) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1806781116 · Cited by 947 · cited 1× · see citing works
“Recognizing the potentially disastrous consequences of letting misinformation proliferate on social media, researchers from diverse fields have proposed a variety of countermeasures, including technological solutions aimed at limiting exposure to misinformation, educational interventions aimed at empowering people to…”
BackgroundDebunking: A Meta-Analysis of the Psychological Efficacy of Messages Countering Misinformation
Chan, M.-P. S., Jones, C. R., Hall Jamieson, K., & Albarracín, D. (2017) · Psychological Science · doi:10.1177/0956797617714579 · Cited by 898 · see citing works
Countering Misinformation and Fake News Through Inoculation and Prebunking
Lewandowsky, S., & van der Linden, S. (2021) · European Review of Social Psychology · doi:10.1080/10463283.2021.1876983 · Cited by 773 · see citing works
See Something, Say Something: Correction of Global Health Misinformation on Social Media
Bode, L., & Vraga, E. (2018) · Health Communication · doi:10.1080/10410236.2017.1331312 · Cited by 691 · see citing works
Bode, L., & Vraga, E. K. (2015) · Journal of Communication · doi:10.1111/jcom.12166 · Cited by 666 · see citing works
Investigating an alternate form of the cognitive reflection test
Thomson, K. S., & Oppenheimer, D. M. (2016) · Judgment and Decision Making · doi:10.1017/s1930297500007622 · Cited by 612 · see citing works
Sources of the continued influence effect: when misinformation in memory affects later inferences
Johnson, H. M., & Seifert, C. M. (1994) · Journal of Experimental Psychology: Learning, Memory, and Cognition · doi:10.1037/0278-7393.20.6.1420 · Cited by 560 · see citing works
Using Expert Sources to Correct Health Misinformation in Social Media
Vraga, E. K., & Bode, L. (2017) · Science Communication · doi:10.1177/1075547017731776 · Cited by 559 · see citing works
Walter, N., & Tukachinsky, R. (2020) · Communication Research · doi:10.1177/0093650219854600 · Cited by 522 · see citing works
Citizens Versus the Internet: Confronting Digital Challenges With Cognitive Tools
Kozyreva, A., Lewandowsky, S., & Hertwig, R. (2020) · Psychological Science in the Public Interest · doi:10.1177/1529100620946707 · Cited by 479 · see citing works
Explicit warnings reduce but do not eliminate the continued influence of misinformation
Ecker, U. K. H., Lewandowsky, S., & Tang, D. (2010) · Memory & Cognition · doi:10.3758/mc.38.8.1087 · Cited by 478 · see citing works
How warnings about false claims become recommendations
Skurnik, I., Yoon, C., Park, D. C., & Schwarz, N. (2005) · Journal of Consumer Research · doi:10.1086/426605 · Cited by 446 · see citing works
van der Meer, T. G. L. A., & Jin, Y. (2019) · Health Communication · doi:10.1080/10410236.2019.1573295 · Cited by 432 · see citing works
Lee, J. J., Kang, K., Wang, M. P., Zhao, S. Z., Wong, J. Y. H., O’Connor, S., Yang, S. C., & Shin, S. H. (2020) · Journal of Medical Internet Research · doi:10.2196/22205 · Cited by 317 · see citing works
Where We Go From Here: Health Misinformation on Social Media
Chou, W. S., Gaysynsky, A., & Cappella, J. N. (2020) · American Journal of Public Health · doi:10.2105/ajph.2020.305905 · Cited by 311 · see citing works
Vraga, E. K., & Bode, L. (2017) · Information Communication & Society · doi:10.1080/1369118x.2017.1313883 · Cited by 308 · see citing works
Mobile, social, and wearable computing and the evolution of psychological practice.
Morris, M. E., & Aguilera, A. (2012) · Professional Psychology Research and Practice · doi:10.1037/a0029041 · Cited by 294 · see citing works
Effective strategies for rebutting science denialism in public discussions
Schmid, P., & Betsch, C. (2019) · Nature Human Behaviour · doi:10.1038/s41562-019-0632-4 · Cited by 264 · see citing works
Making the Truth Stick & the Myths Fade: Lessons from Cognitive Psychology
Schwarz, N., Newman, E., & Leach, W. (2016) · Behavioral Science & Policy · doi:10.1353/bsp.2016.0009 · Cited by 203 · see citing works
A Measure of Perceived Argument Strength: Reliability and Validity
Zhao, X., Strasser, A. A., Cappella, J. N., Lerman, C. E., & Fishbein, M. (2011) · Communication Methods and Measures · doi:10.1080/19312458.2010.547822 · Cited by 200 · see citing works
Correction as a Solution for Health Misinformation on Social Media
Vraga, E. K., & Bode, L. (2020) · American Journal of Public Health · doi:10.2105/ajph.2020.305916 · Cited by 186 · see citing works
SARKISSIAN, H., PARK, J., TIEN, D., WRIGHT, J. C., & KNOBE, J. (2011) · Mind & Language · doi:10.1111/j.1468-0017.2011.01428.x · Cited by 184 · see citing works
Tan, A. S. L., Lee, C., & Chae, J. (2015) · Journal of Communication · doi:10.1111/jcom.12163 · Cited by 181 · see citing works
Addressing COVID-19 Misinformation on Social Media Preemptively and Responsively
Vraga, E. K., & Bode, L. (2021) · Emerging infectious diseases · doi:10.3201/eid2702.203139 · Cited by 163 · see citing works
Vraga, E. K., Kim, S. C., & Cook, J. (2019) · Journal of Broadcasting & Electronic Media · doi:10.1080/08838151.2019.1653102 · Cited by 162 · see citing works
Mask adherence and rate of COVID-19 across the United States
Fischer, C. B., Adrien, N., Silguero, J. J., et al. (2021) · PLoS ONE · doi:10.1371/journal.pone.0249891 · Cited by 151 · see citing works
Going viral: doctors must tackle fake news in the covid-19 pandemic
O’Connor, C., & Murphy, M. (2020) · BMJ · doi:10.1136/bmj.m1587 · Cited by 131 · see citing works
Correcting misinformation by health organizations during measles outbreaks: A controlled experiment
Gesser‐Edelsburg, A., Diamant, A., Hijazi, R., & Mesch, G. S. (2018) · PLoS ONE · doi:10.1371/journal.pone.0209505 · Cited by 120 · see citing works
Evaluation of a template for countering misinformation—Real-world Autism treatment myth debunking
Paynter, J. M., Luskin-Saxby, S., Keen, D., Fordyce, K., Frost, G., Imms, C., Miller, S., Trembath, D. L., Tucker, M. N., & Ecker, U. K. H. (2019) · PLoS ONE · doi:10.1371/journal.pone.0210746 · Cited by 119 · see citing works
A Call for a Public Health Agenda for Social Media Research
Pagoto, S., Waring, M. E., & Xu, R. (2019) · Journal of Medical Internet Research · doi:10.2196/16661 · Cited by 112 · see citing works
Image of mass media news sources
McCroskey, J. C., & Jenson, T. A. (1975) · Journal of Broadcasting · doi:10.1080/08838157509363777 · Cited by 103 · see citing works
Chang, C. (2015) · Science Communication · doi:10.1177/1075547015597914 · Cited by 94 · see citing works
Nagler, R. H., Yzer, M. C., & Rothman, A. J. (2018) · Annals of Behavioral Medicine · doi:10.1093/abm/kay098 · Cited by 90 · see citing works
Lee, C., Nagler, R. H., & Wang, N. (2017) · Health Communication · doi:10.1080/10410236.2016.1278495 · Cited by 89 · see citing works
Vraga, E. K., Bode, L., & Tully, M. (2021) · Health Communication · doi:10.1080/10410236.2021.1910165 · Cited by 84 · see citing works
Bautista, J. R., Zhang, Y., & Gwizdka, J. (2021) · JMIR Public Health and Surveillance · doi:10.2196/27715 · Cited by 72 · see citing works
Luk, T. T., Zhao, S. Z., Weng, X., Wong, J. Y. H., Wu, Y. S., Ho, S. Y., Lam, T. H., & Wang, M. P. (2020) · Tobacco Control · doi:10.1136/tobaccocontrol-2020-055960 · Cited by 70 · see citing works
The Influence of Social Interaction on Intuitions of Objectivity and Subjectivity
Fisher, M., Knobe, J., Strickland, B., & Keil, F. C. (2016) · Cognitive Science · doi:10.1111/cogs.12380 · Cited by 64 · see citing works
Counteracting Health Misinformation
Armstrong, P. W., & Naylor, C. D. (2019) · JAMA · doi:10.1001/jama.2019.5168 · Cited by 63 · see citing works
The Persistence and Peril of Misinformation
(2017) · American Scientist · doi:10.1511/2017.105.6.372 · Cited by 60 · see citing works
Nagler, R. H., Vogel, R. I., Gollust, S. E., Yzer, M. C., & Rothman, A. J. (2021) · Annals of Behavioral Medicine · doi:10.1093/abm/kaab069 · Cited by 58 · see citing works
Nan, X., & Daily, K. (2015) · Journal of Health Communication · doi:10.1080/10810730.2014.989343 · Cited by 55 · see citing works
Prevalence and source analysis of COVID-19 misinformation in 138 countries
Al-Zaman, M. S. (2021) · IFLA Journal · doi:10.1177/03400352211041135 · Cited by 55 · see citing works
Getting Social: Physicians Can Counteract Misinformation With an Online Presence
Rubin, R. (2019) · JAMA · doi:10.1001/jama.2019.10779 · Cited by 24 · see citing works
Setting the Record Straight: Vaccines, Autism, and the Lancet
Ratzan, S. C. (2010) · Journal of Health Communication · doi:10.1080/10810731003780714 · Cited by 14 · see citing works
Medical misinformation and the internet: a call to arms
Gunter, J. (2019) · The Lancet · doi:10.1016/s0140-6736(19)31206-1 · Cited by 4 · see citing works
Flagged first, then by citations
Research works printed but not linked: 1
- [45]Clapper JR Facts and fears: hard truths from a life in intelligence 2018 New York Viking Penguin
Cited by
Sorted by citations
Social Media Role and Its Impact on Public Health: A Narrative Review
Kanchan, S., & Gaidhane, A. (2023) · Cureus · doi:10.7759/cureus.33737 · Cited by 221 · see citing works
“Although debunking research has demonstrated that well-designed corrections can reduce the effects of false information, nothing is known about the effects of correction in the context of protracted social media arguments [46].”
BackgroundKisa, S., & Kisa, A. (2024) · Journal of Medical Internet Research · doi:10.2196/56931 · Cited by 132 · see citing works
Ishizumi, A., Kolis, J., Abad, N., Prybylski, D., Brookmeyer, K. A., Voegeli, C., Wardle, C., & Chiou, H. (2024) · The Lancet Public Health · doi:10.1016/s2468-2667(24)00031-8 · Cited by 79 · see citing works
- Authors
- Mourali, M., & Drake, C.
- Affiliations
- University of Calgary (CA)
- North Central College (US)
- Corresponding author
- Mourali, Mehdi
- Venue
- Journal of Medical Internet Research
- Publisher
- JMIR Publications Inc.
- Published
- 2022-03-02
- Volume
- 24
- Issue
- 3
- Pages
- e34831
- ISSN
- 1438-8871 (ISSN-L)
- PMC
- PMC8893717
- OpenAlex
- W4213142308
- Cited by
- 55
- References
- 64
- Citations by year
- 2026: 8 · 2025: 25 · 2024: 11 · 2023: 8 · 2022: 3
- FWCI
- 16.91
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- cc-by
- Locations
- Journal of Medical Internet Research (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
- Topics
- Social Sciences › Sociology and Political Science › Misinformation and Its Impacts
- Social Sciences › Communication › Communication and COVID-19 Impact
- Social Sciences › Decision Sciences › Information Systems and Management › Academic Publishing and Open Access
- Keywords
- ING, health misinformation, social media debate, COVID-19 pandemic, face masks, rebuke, attitudes and intentions, science communication, washout effect, sharing intention, healthcare workers, public trust in science
- MeSH terms
- COVID-19, SARS-CoV-2, Communication, Humans, Pandemics, Social Media
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review