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Although people have been repeatedly found to underestimate frequencies of common illnesses and overestimate those of rare illnesses, not much is known about this consistent bias in risk perception, termed “primary bias” in the literature, as well as the origin of its variations among different subpopulations. To fill this gap, we conducted a national survey among a representative sample of the French population ( n  = 3,245) to compare the perceived and actual prevalence of chronic illnesses, and to test the hypothesis that numeracy may play an important role in the accuracy of judgments of risk frequencies. The participants were asked to complete a 10-items numeracy scale and to estimate the prevalence of a variety of social conditions and chronic illnesses such as cancers or heart diseases by using a percentage scale. The analyses show that (1) participants tend to greatly overestimate the prevalence of conditions affecting small percentages of people, and underestimate those affecting a large percentage of them, (2) the Tversky and Kahneman’s probability weighting function provides an adequate model to represent the discrepancy between the perceived and actual prevalence of these illnesses or occupations, and (3) the magnitude of the primary bias varies principally as a function of the respondents’ numeracy. These results suggest that the primary bias that affects perceptions of prevalence of chronic diseases is not fundamentally different from those characterizing other types of probabilistic judgments. They also confirm that numeracy plays a considerable role in people’s ability to transform epidemiological observations from their social environment into more accurate estimates.

Revisiting the primary bias: the role of innumeracy in the misperception of prevalence of chronic illnesses