Misinformation has deleterious and potentially destabilizing effects on democracy. As a result, scholars and practitioners alike are investigating strategies to reduce the belief in and dissemination of misinformation. A common strategy is a digital literacy intervention to increase individual capacity to identify misinformation online. This, we argue, ignores identity-based motivations to consume biased media. We offer a theoretical framework that highlights the limitations of strategies that ignore individuals’ directional motives. We propose three interventions that leverage insights on how social identity shapes behavior, and test each with an information experiment in Côte d’Ivoire, a polarized country. We find that a standard digital literacy intervention fails to curb the belief in and spread of misinformation, while our social-identity-based interventions limited both. Our findings confirm that misinformation spreads at least in part because individuals are motivated to consume biased media, and caution against strategies that ignore these directional motives.

Voters may be unable to hold politicians to account if they lack basic information about their representatives' performance. Civil society groups and international donors therefore advocate using voter information campaigns to improve democratic accountability. Yet, are these campaigns effective? Limited replication, measurement heterogeneity, and publication biases may undermine the reliability of published research. We implemented a new approach to cumulative learning, coordinating the design of seven randomized controlled trials to be fielded in six countries by independent research teams. Uncommon for multisite trials in the social sciences, we jointly preregistered a meta-analysis of results in advance of seeing the data. We find no evidence overall that typical, nonpartisan voter information campaigns shape voter behavior, although exploratory and subgroup analyses suggest conditions under which informational campaigns could be more effective. Such null estimated effects are too seldom published, yet they can be critical for scientific progress and cumulative, policy-relevant learning.