Skip to main content

ETHNOS_APP

Home • Search • Journals • List 0

Who Is Susceptible to Online Health Misinformation

Bibliographic Data

ID11032142
AuthorsLaura D Scherer (0000-0002-8660-7115, Laura D. Scherer is with the Division of Cardiology and the Adult & Child Consortium for Health Outcomes Research and Delivery Science, University of Colorado, Denver. Gordon Pennycook is with the Department of Psychology, University of Regina, Regina, SK.), Gordon Pennycook (0000-0003-1344-6143, Laura D. Scherer is with the Division of Cardiology and the Adult & Child Consortium for Health Outcomes Research and Delivery Science, University of Colorado, Denver. Gordon Pennycook is with the Department of Psychology, University of Regina, Regina, SK.)
Year2020
Volume110
IssueS3
PagesS276-S277
Publication date2020-10-01
Peer ReviewedYes
Open AccessNo
TypeARTICLE
VenueAmerican Journal of Public Health (JOURNAL)
Journal identifiersISSN: 0090-0036 • E-ISSN: 1541-0048
PublisherAmerican Public Health Association (PUBLISHER • US)
DOI10.2105/ajph.2020.305908
PMID33001736
OpenAlexW3090167452
LanguageEN
Citations received13
References cited6

[ ]Guess et al recently reported that a brief digital media literacy intervention improved detection of fake news headlines in both the United States and India 2 Another perspective is that people tend to be susceptible to misinformation that is consistent with their preexisting beliefs or worldview 3 Considerable research has shown that people tend to preferentially believe information that is consistent with their other preexisting beliefs 3 However, recent research has found that people may not be as influenced by their preexisting attitudes as previously thought [ ]a recent study showed that a simple accuracy nudge that primes people to think about whether headlines are true is sufficient to increase the quality of COVID-19-related news content that people indicate they would share on social media 5 A Twitter field experiment employing a similar intervention has also reported promising results 7 These findings support the idea that people fall for misinformation because they fail to think about the accuracy of content that they come across on social media, not because they are exercising politically motivated reasoning or are simply confused about what is and is not true To summarize, there are three currently dominant (albeit not entirely mutually exclusive) theoretical perspectives addressing why certain people are susceptible to online misinformation: (1) being confused about what is true versus false, suggesting that knowledge or various literacies are a primary factor;(2) having strong preexisting beliefs or ideological motivations that lead to motivated reasoning and therefore a desire to believe and share misinformation;and (3) neglecting to sufficiently reflect about the truth or accuracy of news content that is encountered on social media

Health care · Health literacy · Ideology · Internet privacy · Intervention (counseling) · Misinformation · Perspective (graphical) · Political science · Politics · Psychiatry · Social media · Computer Science · Hate Speech and Cyberbullying Detection · Misinformation and Its Impacts · Psychology · Social Media and Politics · Social Psychology

  • How Health-Related Misinformation Spreads Across the Internet

    Open Access•Lei Zheng, Jincheng Cai et al.•Cyberpsychology Behavior and…•2022

  • Fighting cheapfakes

    Open Access•Sijia Qian, Cuihua Shen et al.•Journal of Computer-Mediated…•2022

  • What is the impact of artificial intelligence-based chatbots on infodemic management

    Open Access•Plinio Pelegrini Morita, Marta Lotto et al.•Frontiers in Public Health•2024

  • Age differences in susceptibility to stroke-related health misinformation on social media

    Open Access•Hongkai Li, Xingyun Liu et al.•Frontiers in Public Health•2026

  • Social Media Use and Misinformation Among Asian Americans During Covid-19

    Open Access•Stella K Chong, Shahmir H Ali et al.•Frontiers in Public Health•2022

  • How People Process Different Types of Health Misinformation

    Xinyan Zhao, Stephanie Jean Tsang•Health Communication•2024

  • Why Do People Believe in Vaccine Misinformation? The Roles of Perceived Familiarity and Evidence Type

    Yuming Fang•Health Communication•2024

  • Trust but verify? Examining the role of trust in institutions in the spread of unverified information on social media

    Open Access•Ward Van Zoonen, Vilma Luoma‐aho et al.•Computers in Human Behavior•2024

  • Who shares misinformation on social media? A meta-analysis of individual traits related to misinformation sharing

    Open Access•Juan Xie, Yanqing Sun•Computers in Human Behavior•2024

  • The pursuit of online misinformation literacy

    Open Access•Junyeong Lee, Jung Lee et al.•Telematics and Informatics•2025

  • Developing digital health literacy amidst the Covid-19 infodemic

    Open Access•Rosita Maglie, Rosita Belinda Maglie et al.•Translation and Translanguaging…•2024

  • Self-diagnosis in the age of social media

    Open Access•Sarah Armstrong, Elizabeth Osuch et al.•Acta Psychologica•2025

  • Missing Voices

    Open Access•Michelle A Amazeen, Rosalynn A Vasquez et al.•Science Communication•2024

  • Lazy, not biased

    Open Access•Gordon Pennycook, David Rand et al.•Cognition•2018

  • Aging in an Era of Fake News

    Open Access•Nadia M Brashier, Daniel L Schacter•Current Directions in Psychological…•2020

  • Fighting Covid-19 Misinformation on Social Media

    Open Access•Gordon Pennycook, Jonathon Mcphetres et al.•Psychological Science•2020

  • Who falls for fake news? The roles of bullshit receptivity, overclaiming, familiarity, and analytic thinking

    Open Access•Gordon Pennycook, David G Rand et al.•Journal of Personality•2020

Unique citing works13
Citations per year3,25
Citation span2022 - 2026 (5)
Citation velocitycurrent
Highly citedNo
Citation typesNeutral: 12
Ethnos_APP • Open Source Project • MIT License • Frontend v2.0.0 • Privacy and Cookies • API Documentation: api.ethnos.app/docs • API Source Code: GitHub • DOI: 10.5281/zenodo.17049435 • Frontend Source Code: GitHub • DOI: 10.5281/zenodo.17050053 • cruz.rio.br • Expectantes Misericordiae