The impact of social norms on health‐related belief update
Abstract
People are constantly bombarded with information they could use to adjust their beliefs. Here, we are interested in exploring the impact of social norms on health-related belief update. To investigate, we recruited a sample of 200 Princeton University students, who first rated the accuracy of a set of health statements (pre-test). They were then provided with relevant evidence either in favor or against the initial statements, and were asked to rate how convincing each piece of evidence was. The evidence was randomly assigned to appear as normative or non-normative, and anecdotal or scientific. Finally, participants rated the accuracy of the initial set of statements again (post-test). The results show that participants rationally updated their beliefs more when the evidence was scientific compared to when it was anecdotal. More importantly to our primary inquiry, the results show that participants changed their beliefs more in line with the evidence when the evidence was portrayed as normative compared to when the evidence was portrayed as non-normative, pointing to the impactful influence social norms have on health beliefs. Both effects were mediated by participants' subjective evaluation of the convincingness of the evidence, indicating the mechanism by which evidence is selectively incorporated into belief systems.
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When people know that others have seen and approved of particular viewpoints, they are more likely to adopt those viewpoints themselves.
“When people know that others have seen and approved of particular viewpoints, they are more likely to adopt those viewpoints themselves (Vlasceanu & Coman, 2022).”
From Stories in Action. (2022) · cites this paper as Vlasceanu & Coman, 2022
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
“Their detrimental effects have increased over time with the advancements in technology that facilitate the faster spread of false information compared to accurate information (Vosoughi et al., 2018).”
BackgroundMisinformation 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
Pennycook, G., McPhetres, J., Zhang, Y., Lu, J. G., & Rand, D. G. (2020) · Psychological Science · doi:10.1177/0956797620939054 · Cited by 1,715 · see citing works
Word of mouth and interpersonal communication: A review and directions for future research
Berger, J. (2014) · Journal of Consumer Psychology · doi:10.1016/j.jcps.2014.05.002 · Cited by 1,469 · see citing works
The Effects of Anti-Vaccine Conspiracy Theories on Vaccination Intentions
Jolley, D., & Douglas, K. M. (2014) · PLoS ONE · doi:10.1371/journal.pone.0089177 · Cited by 1,232 · cited 1× · see citing works
“…can have destructive outcomes in all aspects of society, as concluded by numerous empirical articles linking false beliefs to decreased vaccination rates (Jolley & Douglas, 2014), increased climate change denial (Lewandowsky et al., 2015), and increased intergroup prejudice (Jolley et al., 2020).”
BackgroundInoculating the Public against Misinformation about Climate Change
van der Linden, S., Leiserowitz, A., Rosenthal, S., & Maibach, E. (2017) · Global Challenges · doi:10.1002/gch2.201600008 · Cited by 1,058 · see citing works
Exposure to intergroup conspiracy theories promotes prejudice which spreads across groups
Jolley, D., Meleady, R., & Douglas, K. M. (2020) · British Journal of Psychology · doi:10.1111/bjop.12385 · Cited by 268 · cited 1× · see citing works
“, 2015), and increased intergroup prejudice (Jolley et al., 2020).”
The Robust Relationship Between Conspiracism and Denial of (Climate) Science
Lewandowsky, S., Gignac, G. E., & Oberauer, K. (2015) · Psychological Science · doi:10.1177/0956797614568432 · Cited by 88 · see citing works
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The psychological drivers of misinformation belief and its resistance to correction
Ecker, U. K. H., Lewandowsky, S., Cook, J., Schmid, P., Fazio, L. K., Brashier, N., Kendeou, P., Vraga, E. K., & Amazeen, M. A. (2022) · Nature Reviews Psychology · doi:10.1038/s44159-021-00006-y · Cited by 1,372 · see citing works
Walsh, J., Vaida, N., Coman, A., & Fiske, S. T. (2022) · Psychological Science in the Public Interest · doi:10.1177/15291006231161337 · Cited by 26 · see citing works
“When people know that others have seen and approved of particular viewpoints, they are more likely to adopt those viewpoints themselves (Vlasceanu & Coman, 2022).”
BackgroundSelf-citation
- Authors
- Vlasceanu, M., & Coman, A.
- Affiliations
- Princeton University (US)
- Corresponding author
- Vlasceanu, Madalina
- Venue
- Applied Psychology: Health and Well-Being
- Publisher
- Wiley
- Published
- 2021-10-13
- Volume
- 14
- Issue
- 2
- Pages
- 453-464
- ISSN
- 1758-0846 (ISSN-L)
- 1758-0854
- OpenAlex
- W3207580517
- Cited by
- 38
- References
- 8
- Citations by year
- 2026: 3 · 2025: 16 · 2024: 5 · 2023: 7 · 2022: 7
- FWCI
- 45.52
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Applied Psychology Health and Well-Being (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Social Sciences › Arts and Humanities › Literature and Literary Theory › Media Influence and Health
- Social Sciences › Decision Sciences › General Decision Sciences › Decision-Making and Behavioral Economics
- Social Sciences › Sociology and Political Science › Risk Perception and Management
- Keywords
- social norms, belief updating, health beliefs, anecdotal evidence, scientific evidence, health misinformation, belief accuracy
- MeSH terms
- Humans, Social Norms
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