Searching for the backfire effect: Measurement and design considerations.
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their belief in the very misconception the correction is aiming to rectify. There is currently a debate in the literature as to whether backfire effects exist at all, as recent studies have failed to find the phenomenon, even under theoretically favorable conditions. In this review, we summarize the current state of the worldview and familiarity backfire effect literatures. We subsequently examine barriers to measuring the backfire phenomenon, discuss approaches to improving measurement and design, and conclude with recommendations for fact-checkers. We suggest that backfire effects are not a robust empirical phenomenon, and more reliable measures, powerful designs, and stronger links between experimental design and theory could greatly help move the field ahead.
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A growing number of empirical studies have uncovered evidence that people update their political attitudes and beliefs in line with evidence and arguments presented to them.
“Consistent with this view, a growing number of empirical studies have uncovered evidence that people update their political attitudes and beliefs in line with evidence (e.g., refs. 4,13,27–29) and arguments23,30,31 presented to them.”
From Factual knowledge can reduce attitude polarization (2025) · cites this paper as [29]
Researchers have studied a backfire effect in which an intervention attempting to change an individual's belief ends up reinforcing their belief.
“Researchers have also studied the backfire effect, in which an intervention attempting to change an individual's belief ends up reinforcing their belief (Swire-Thompson, DeGutis, and Lazer 2020).”
From Epistemic Injustice in Generative AI (2024) · cites this paper as Swire-Thompson, DeGutis, and Lazer 2020
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- Authors
- Swire-Thompson, B., DeGutis, J., & Lazer, D.
- Affiliations
- Harvard University (US)
- Northeastern University (US)
- Venue
- Journal of Applied Research in Memory and Cognition
- Published
- 2020-09
- Volume
- 9
- Issue
- 3
- Pages
- 286-299
- ISSN
- 2211-3681 (ISSN-L)
- 2211-369X
- PMC
- PMC7462781
- OpenAlex
- W3082187871
- Cited by
- 360
- References
- 92
- Citations by year
- 2026: 35 · 2025: 39 · 2024: 109 · 2023: 62 · 2022: 62 · 2021: 41 · 2020: 12
- FWCI
- 7.82
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Locations
- Journal of Applied Research in Memory and Cognition (publishedVersion, other-oa)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- PsyArXiv (OSF Preprints) (submittedVersion)
- PsyArXiv (OSF Preprints) (submittedVersion, cc-by)
- Funders
- Hewlett Packard Foundation
- Topics
- Social Sciences › Sociology and Political Science › Misinformation and Its Impacts
- Social Sciences › Sociology and Political Science › Social and Intergroup Psychology
- Social Sciences › Decision Sciences › General Decision Sciences › Decision-Making and Behavioral Economics
- Keywords
- backfire effect, fact-checking, misinformation correction, belief revision, experimental design, fact-checkers
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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