Proceedings of the Annual Meeting of the Cognitive Science Society

Cognitive science offers powerful tools for addressing pressing public health needs. In the current line of work, 1700 US parents reported beliefs about a range of topics related to pediatric COVID vaccination. We deployed Bayesian network structure learning to develop a cognitive model of the relationships among these beliefs and their combined influence on vaccine endorsement. Nine months later, we re-measured these beliefs in a subset of returning participants (n=884) to examine how beliefs changed together over a particularly tumultuous period of time. In a simple comparison of observed co-changes to Time 1 correlations, as well as a comparison of co-changes to model-based simulations, the relationships among beliefs at Time 1 accurately predicted co-change over time (R2 .84-.92 across models). This is consistent with the possibility that correlations across individuals at a single timepoint reflect an underlying belief network that also governs how beliefs change over time.