ArticleNature human behaviour2024
Fact-checker warning labels are effective even for those who distrust fact-checkers.
Article in Nature human behaviour, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
8 citing papers in PubMed.
- As Social Media Scales Back Fact-Checking, Can Technologies Fill the Gap?Journal of medical Internet research · 2026Article
- How social learning enhances-or undermines-efficiency and flexibility in collective decision-making under uncertainty.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Community notes reduce engagement with and diffusion of false information online.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Labeling AI-generated media online.PNAS nexus · 2025Article
- Perceived legitimacy of layperson and expert content moderators.PNAS nexus · 2025Article
- People adhere to content warning labels even when they are wrong due to ecologically rational adaptations.Scientific reports · 2025Article
- How rational inference about authority debunking can curtail, sustain, or spread belief polarization.PNAS nexus · 2024Article
- Community notes increase trust in fact-checking on social media.PNAS nexus · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
Abstract
Warning labels from professional fact-checkers are one of the most widely used interventions against online misinformation. But are fact-checker warning labels effective for those who distrust fact-checkers? Here, in a first correlational study (N = 1,000), we validate a measure of trust in fact-checkers. Next, we conduct meta-analyses across 21 experiments (total N = 14,133) in which participants evaluated true and false news posts and were randomized to either see no warning labels or to see warning labels on a high proportion of the false posts. Warning labels were on average effective at reducing belief in (27.6% reduction), and sharing of (24.7% reduction), false headlines. While warning effects were smaller for participants with less trust in fact-checkers, warning labels nonetheless significantly reduced belief in (12.9% reduction), and sharing of (16.7% reduction), false news even for those most distrusting of fact-checkers. These results suggest that fact-checker warning labels are a broadly effective tool for combatting misinformation.
Indexed as
Identifiers
39223352What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.