Our central question is: how accurate are laypeople’sstatistical intuitions about probability distributions within thedomain of health? Specifically, can participants produceentire probability distributions for the duration of illnesses?While a large body of decision making research has suggestedthat people use a flawed process to arrive at decisions, weposit that participants may be using an optimal process, butwith flawed information. To this end, we assess accuracy interms of both the mean and form of distributions for bothacute illnesses for which people might have experience, andchronic conditions for which people are less likely to haveexperience. We find that participants can accurately estimatethe mean and form of distributions for acute illnesses.

People’s predictions for real-world events have been shown tobe well-calibrated to the true environmental statistics (e.g.Griffiths and Tenenbaum 2006). Previous work, however, hasfocused on predictions for these events by aggregating acrossobservers, making a single estimate for the total durationgiven a current duration. Here, we focus on assessingpredictions for both the mean and form of distributions in thedomain of illness duration prediction at the individual level.We assess understanding for both acute illnesses for whichpeople might have experience, as well as chronic conditionsfor which people are less likely to have knowledge. Our datasuggests that for common acute illnesses people canaccurately estimate both the mean and form of thedistribution. For less common acute illnesses and chronicillnesses, people have a tendency to overestimate the meanduration, but still accurately predict the distribution form.

People make accurate predictions for many real world events e.g. human life spans (Griffiths & Tenenbaum, 2006).Accurate predictions are particularly important in the domain of health, where illness knowledge directly influences patientoutcomes. To understand how well peoples’ illness expectations were aligned, we asked participants to estimate durationsfor 9 illnesses, and compared their responses to the real-world distributions. We found that for common acute illnesses (e.g.,the cold) people make accurate predictions, whereas for rare chronic illnesses (e.g., COPD) people make comparatively poorpredictions. Further, we found that participants overestimate the prevalence of every illness, especially for those that are morecommon (e.g., the cold). Taken together, these results suggest that people more accurately estimate the duration of commonacute illnesses, but this may cause them to overestimate the prevalence of these illnesses. Results will be discussed in terms ofimplications for both cognition and behavioral health theory.