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Abstract
Corrections are a frequently used and effective tool for countering misinformation. However, concerns have been raised that corrections may introduce false claims to new audiences when the misinformation is novel. This is because boosting the familiarity of a claim can increase belief in that claim, and thus exposing new audiences to novel misinformation—even as part of a correction—may inadvertently increase misinformation belief. Such an outcome could be conceptualized as a familiarity backfire effect, whereby a familiarity boost increases false-claim endorsement above a control-condition or pre-correction baseline. Here, we examined whether standalone corrections—that is, corrections presented without initial misinformation exposure—can backfire and increase participants’ reliance on the misinformation in their subsequent inferential reasoning, relative to a no-misinformation, no-correction control condition. Across three experiments (total N = 1156) we found that standalone corrections did not backfire immediately (Experiment 1) or after a one-week delay (Experiment 2). However, there was some mixed evidence suggesting corrections may backfire when there is skepticism regarding the correction (Experiment 3). Specifically, in Experiment 3, we found the standalone correction to backfire in open-ended responses, but only when there was skepticism towards the correction. However, this did not replicate with the rating scales measure. Future research should further examine whether skepticism towards the correction is the first replicable mechanism for backfire effects to occur.
Original language | English |
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Article number | 39 |
Journal | Cognitive Research: Principles and Implications |
Volume | 8 |
Issue number | 1 |
DOIs | |
Publication status | Published - Dec 2023 |
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Dive into the research topics of 'Examining the replicability of backfire effects after standalone corrections'. Together they form a unique fingerprint.Projects
- 1 Finished
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Combating Misinformation – Designing a Toolkit to Address a Global Problem
Ecker, U. (Investigator 01)
ARC Australian Research Council
27/07/20 → 26/07/24
Project: Research