This will be a hybrid in-person and remote talk.

Misinformation correction interventions often rely on factorial randomized control trials (RCT) to assess message effectiveness. Sample size constraints, however, limit the number of interventions researchers can evaluate via RCTs. Conjoint experiments – which ask respondents to render judgments about several stimuli with many different attribute combinations – could resolve this problem, but are complicated by implementation difficulties. I offer a novel framework for applying conjoint designs to misinformation correction, and offer two demonstrations of their viability: one addressing misinformation in three domains (climate change, COVID-19 vaccination, genetically modified food), and another in a single domain (flu vaccine beliefs). In addition to establishing methodological viability, I document strong levels of misinformation correction across studies. I also build on prior research by providing preliminary evidence that, under some conditions, validating misinformed beliefs can inspire attitudinal change.  I conclude by outlining how conjoint experiments can help to more-efficiently evaluate misinformation correction communications.