Explicit Predictions for Illness Statistics

Abstract

People’s predictions for real-world events have been shown to be well-calibrated to the true environmental statistics (e.g. Griffiths and Tenenbaum 2006). Previous work, however, has focused on predictions for these events by aggregating across observers, making a single estimate for the total duration given a current duration. Here, we focus on assessing predictions for both the mean and form of distributions in the domain of illness duration prediction at the individual level. We assess understanding for both acute illnesses for which people might have experience, as well as chronic conditions for which people are less likely to have knowledge. Our data suggests that for common acute illnesses people can accurately estimate both the mean and form of the distribution. For less common acute illnesses and chronic illnesses, people have a tendency to overestimate the mean duration, but still accurately predict the distribution form.


Back to Table of Contents