Debunking: A Meta-Analysis of the Psychological Efficacy of Messages Countering Misinformation
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This meta-analysis investigated the factors underlying effective messages to counter attitudes and beliefs based on misinformation. Because misinformation can lead to poor decisions about consequential matters and is persistent and difficult to correct, debunking it is an important scientific and public-policy goal. This meta-analysis ( k = 52, N = 6,878) revealed large effects for presenting misinformation ( ds = 2.41–3.08), debunking ( ds = 1.14–1.33), and the persistence of misinformation in the face of debunking ( ds = 0.75–1.06). Persistence was stronger and the debunking effect was weaker when audiences generated reasons in support of the initial misinformation. A detailed debunking message correlated positively with the debunking effect. Surprisingly, however, a detailed debunking message also correlated positively with the misinformation-persistence effect.
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Meta-analytic studies show that corrections are generally effective in reducing misperceptions.
“meta-analytic studies show that corrections are generally effective in reducing misperceptions (Chan et al., 2017;Walter and Murphy, 2018).”
From Factual belief polarization between Democrats and Republicans: source or epiphenomenon of ideological and affective polarization? (2024) · cites this paper as Chan et al., 2017
Misinformation often persists after being exposed to corrective messages.
“misinformation often persist after being exposed to corrective messages (Chan et al., 2017)”
From The fingerprints of misinformation: how deceptive content differs from reliable sources in terms of cognitive effort and appeal to emotions (2022) · cites this paper as Chan et al., 2017
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- Authors
- Chan, M.-P. S., Jones, C. R., Hall Jamieson, K., & Albarracín, D.
- Affiliations
- University of Illinois Urbana-Champaign (US)
- University of Pennsylvania (US)
- The Annenberg Public Policy Center, University of Pennsylvania
- Corresponding author
- Chan, Man-pui Sally
- Venue
- Psychological Science
- Publisher
- SAGE Publications
- Published
- 2017-09-12
- Volume
- 28
- Issue
- 11
- Pages
- 1531-1546
- ISSN
- 0956-7976 (ISSN-L)
- 1467-9280
- PMC
- PMC5673564
- OpenAlex
- W2754477858
- Cited by
- 898
- References
- 42
- Citations by year
- 2026: 81 · 2025: 117 · 2024: 112 · 2023: 93 · 2022: 142 · 2021: 114 · 2020: 93 · 2019: 85 · 2018: 58 · 2017: 3
- FWCI
- 20.35
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Psychological Science (publishedVersion)
- Europe PMC (PubMed Central) (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Funders
- National Institute of Mental Health (R01MH094241)
- National Cancer Institute (P50CA179546)
- Topics
- Social Sciences › Sociology and Political Science › Misinformation and Its Impacts
- Social Sciences › Sociology and Political Science › Social and Intergroup Psychology
- Social Sciences › Psychology › Social Psychology › Deception detection and forensic psychology
- Keywords
- debunking, misinformation, belief revision, attitude change, misinformation correction
- MeSH terms
- Attitude, Communication, Humans, Thinking
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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