Causal information changes how we reason: a mixed-methods analysis of decision-making with causal information

Causal information, from health guidance on diets that prevent disease to financial advice for growing savings, is everywhere. Psychological research has shown that people can readily use causal information to make decisions and choose interventions. However, this work has mainly focused on novel systems rather than everyday domains, such as health and finance. Recent research suggests that in familiar scenarios, causal information can lead to worse decisions than having no information at all, but the mechanism behind this effect is not yet known. We aimed to address this by studying whether people reason differently when they receive causal information and whether the type of reasoning affects decision quality. For a set of decisions about health and personal finance, we used quantitative (e.g., decision accuracy) and qualitative (e.g., free-text descriptions of decision processes) methods to capture decision quality and how people used the provided information. We found that participants given causal information focused on different aspects than did those who did not receive causal information and that reasoning linked to better decisions with no information was associated with worse decisions with causal information. Furthermore, people brought in many aspects of their existing knowledge and preferences, going beyond the conclusions licensed by the provided information. Our findings provide new insights into why decision quality differs systematically between familiar and novel scenarios and suggest directions for future work guiding everyday choices.