Examining the replicability of backfire effects after standalone corrections
Toby Prike; Phoebe Blackley; Briony Swire‐Thompson; Ullrich K. H. Ecker · 2023 · Cognitive Research Principles and Implications
WASTE classifies this as Negative / Null Result Report · AI classification, approximate
The study found no significant effect — useful as a negative control or null benchmark for your own design.
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
Abstract by Toby Prike; Phoebe Blackley; Briony Swire‐Thompson; Ullrich K. H. Ecker, Cognitive Research Principles and Implications (2023) — licensed CC BY 4.0.
About to run something similar?
Run an AI Precheck on your own design to catch failure modes like this one before you spend the time. Your first desk check is free.
Related failures
Investigating Variation in Replicability
Negative / Null Result ReportMany Labs 2: Investigating Variation in Replicability Across Samples and Settings
Failed Experiment ReportGetting Ahead in the Communist Party: Explaining the Advancement of Central Committee Members in China
Negative / Null Result ReportReducing implicit racial preferences: II. Intervention effectiveness across time.
Negative / Null Result ReportTHE IMPACT OF IMMIGRATION ON THE STRUCTURE OF WAGES: THEORY AND EVIDENCE FROM BRITAIN
Negative / Null Result ReportRevisiting the Marshmallow Test: A Conceptual Replication Investigating Links Between Early Delay of Gratification and Later Outcomes
WASTE indexes this work — it does not host or republish it. Failure-type classification is automated and approximate.
Metadata source: OpenAlex · DOI 10.1186/s41235-023-00492-z
