Video inoculation against election misinformation across 12 EU nations
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Peer-reviewed
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Abstract
Short video-based prebunking reduces misinformation susceptibility by forewarning viewers about manipulation tactics. However, its effectiveness across older populations (45 + ), diverse cultures, and election-related misinformation remains unclear. To address this, we conducted 13 surveys across 12 EU nations (N = 19,735), testing three inoculation videos developed for the largest prebunking campaign to date, which reached 120M+ YouTube users before the 2024 EU Elections. These videos targeted three widely used misinformation tactics—scapegoating, decontextualization, and discrediting—which were prevalent across EU nations leading up to the elections. The videos improved manipulation (measured through manipulativeness assessments) and technique (measured through the correct identification of tactics) discernment of manipulative content from non-manipulative content and enhanced sharing decisions. Though effects were small (ds ≈ 0.08–0.38), they were significant across surveys. Longer (50s) videos showed more consistent improvements in discernment than shorter (20s) ones, but both improved technique discernment. Moderation analyses revealed country-level (e.g., education index) and socio-demographic (e.g., personal educational attainment) influences that could inform future interventions. These findings demonstrate that scalable video-based inoculation interventions can be deployed to counter election misinformation across nations, but future work should explore how repeated or context-specific prebunking can sustain resistance to misinformation in diverse electoral and media environments.
Description
Acknowledgements: We would like to thank the local translators, data collection teams working with Bilendi, and related survey administrators across all participating EU nations for their invaluable contributions to adapting and implementing the materials in culturally and linguistically appropriate ways. We are also grateful to the Moonshot and Google Jigsaw teams for developing and distributing the prebunking videos tested in this research, and for their logistical support in coordinating the project. This research was supported by Google Jigsaw. The authors thank all study participants for their time and engagement, as well as colleagues at the University of Kent, University of Cambridge, and Moonshot for their feedback during project development.
Publication status: Published
Funder: Google; doi: https://doi.org/10.13039/100006785
Funder: Google Jigsaw

