Misinformation: susceptibility, spread, and interventions to immunize the public
Open accessAbstract
The spread of misinformation poses a considerable threat to public health and the successful management of a global pandemic. For example, studies find that exposure to misinformation can undermine vaccination uptake and compliance with public-health guidelines. As research on the science of misinformation is rapidly emerging, this conceptual Review summarizes what we know along three key dimensions of the infodemic: susceptibility, spread, and immunization. Extant research is evaluated on the questions of why (some) people are (more) susceptible to misinformation, how misinformation spreads in online social networks, and which interventions can help to boost psychological immunity to misinformation. Implications for managing the infodemic are discussed.
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Based on various theories, researchers have identified political orientation, belief in conspiracy theories, and trust in institutions as individual variables that may motivate belief in misinformation.
“Based on various theories, such as the theory of motivated reasoning, which explains that decisions are often based on pre-determined goals and desirability rather than an accurate reflection of the evidence (Kunda, 1990), researchers have identified a few individual variables that may motivate the person to believe misinformation they are exposed to.These include political orientation (Chen et al”
From Deepfakes, Democracy, and the Ethics of Synthetic Media: A Synthesis of the SOLARIS Project (2026) · cites this paper as van der Linden, 2022
The Susceptibility section (page not supplied) identifies political orientation as associated with susceptibility to misinformation, and the motivated-reasoning discussion explains how political identity may shape belief. The paper mentions conspiracy theories as misinformation or intervention targets, but the passages do not identify prior belief in conspiracy theories or trust in institutions as individual variables motivating belief in misinformation. (LLM, conf=0.87)
Experimental — accuracy not yet measuredThe inattention account posits that being bombarded with information, coupled with limited time and resources, interferes with individuals' ability to accurately reflect on content.
“The so-called inattention account posits that being bombarded with information, coupled with limited time and resources, interferes with individuals' ability to accurately reflect on the content (van der Linden, 2022).”
From Deepfakes, Democracy, and the Ethics of Synthetic Media: A Synthesis of the SOLARIS Project (2026) · cites this paper as van der Linden, 2022
Age and social media use may be important in the context of misinformation.
“Starting with sociodemographic variables, previous literature has revealed that age and social media use may be important in the context of misinformation (van der Linden, 2022).”
From Deepfakes, Democracy, and the Ethics of Synthetic Media: A Synthesis of the SOLARIS Project (2026) · cites this paper as van der Linden, 2022
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Facilitating system-level behavioural climate action using computational social science
Debnath, R., van der Linden, S., Alvarez, R. M., & Sovacool, B. K. (2023) · Nature Human Behaviour · doi:10.1038/s41562-023-01527-7 · Cited by 15 · see citing works
Markant, D. B., Rogha, M., Karduni, A., Wesslen, R. S., & Wenwen Dou, A. (2023) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3544548.3581330 · Cited by 16 · see citing works
Impact of misinformation in the evolution of collective cooperation on networks
Meng, Y., Broom, M., & Li, A. (2023) · Journal of The Royal Society Interface · doi:10.1098/rsif.2023.0295 · Cited by 16 · see citing works
Combatting Climate Disinformation: Comparing the Effectiveness of Correction Placement and Type
Christner, C., Merz, P., Barkela, B., Jungkunst, H. F., & von Sikorski, C. (2024) · Environmental Communication · doi:10.1080/17524032.2024.2316757 · Cited by 19 · see citing works
Diverse misinformation: impacts of human biases on detection of deepfakes on networks
Lovato, J., St-Onge, J., Harp, R., Salazar Lopez, G., Rogers, S. P., Haq, I. U., Hébert-Dufresne, L., & Onaolapo, J. (2024) · npj Complexity · doi:10.1038/s44260-024-00006-y · Cited by 16 · see citing works
Zhou, Q., Duan, X., & Yu, G. (2025) · Chaos Solitons & Fractals · doi:10.1016/j.chaos.2025.116498 · Cited by 15 · see citing works
Learning about informal fallacies and the detection of fake news: An experimental intervention
Hruschka, T. M. J., & Appel, M. (2023) · PLoS ONE · doi:10.1371/journal.pone.0283238 · Cited by 16 · see citing works
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- Authors
- van der Linden, S.
- Venue
- Nature Medicine
- Published
- 2022-03
- Volume
- 28
- Issue
- 3
- Pages
- 460-467
- ISSN
- 1078-8956 (ISSN-L)
- 1546-170X
- OpenAlex
- W4220844191
- Cited by
- 570
- References
- 121
- Citations by year
- 2026: 106 · 2025: 130 · 2024: 161 · 2023: 126 · 2022: 47
- FWCI
- 19.53
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Nature Medicine (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Social Sciences › Sociology and Political Science › Misinformation and Its Impacts
- Social Sciences › Communication › Communication and COVID-19 Impact
- Social Sciences › Health › Vaccine Coverage and Hesitancy
- Keywords
- misinformation, infodemic, misinformation susceptibility, misinformation spread, social networking sites, psychological immunity, misinformation interventions, vaccine uptake, public health recommendations, pandemic response
- 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 ›
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