Skip to main content

ETHNOS_APP

Home • Search • Journals • List 0

Revisiting the primary bias

The role of innumeracy in the misperception of prevalence of chronic illnesses

Bibliographic Data

ID12598299
AuthorsJocelyn Raude (0000-0001-8020-4975, Department of Social and Behavioral Sciences, EHESP French School of Public Health, Rennes, France, corresponding author), Christina Xiao (0000-0002-1183-0259, Department of Social and Behavioral Sciences, EHESP French School of Public Health, Rennes, France), Pascal Crépey (0000-0003-1852-0752, Department of Social and Behavioral Sciences, EHESP French School of Public Health, Rennes, France)
Year2022
Volume26
Issue1
Pages64-82
Publication date2022-05-23
Open AccessNo
TypeARTICLE
VenueJournal of Risk Research (JOURNAL)
Journal identifiersISSN: 1366-9877 • E-ISSN: 1466-4461
PublisherRoutledge (PUBLISHER • GB)
DOI10.1080/13669877.2022.2077415
OpenAlexW4281297517
LanguageEN
References cited51

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

Environmental health · Literacy · Numeracy · Population · Sample (material · Weighting · Demography · Health disparities and outcomes · Health Systems, Economic Evaluations, Quality of Life · Medicine · Psychology · Risk Perception and Management · Epidemiology

  • Thinking and Deciding

    Open Access•Jonathan Baron•Thinking and Deciding•2006

  • The Probability Weighting Function

    Drazen Prelec•Econometrica•1998

  • Culture and Identity‐Protective Cognition

    Open Access•Dan M Kahan, Donald Braman et al.•Journal of Empirical Legal Studies•2007

  • The Role of Numeracy in Understanding the Benefit of Screening Mammography

    Open Access•Lisa M Schwartz, Steven Woloshin et al.•Annals of Internal Medicine•1997

  • The Science of Sex Differences in Science and Mathematics

    Open Access•Diane F Halpern, Camilla P Benbow et al.•Psychological Science in the…•2007

  • Curvature of the Probability Weighting Function

    Open Access•George Wu, G Y Wu et al.•Management Science•1996

  • The affect heuristic

    Open Access•Paul Slovic, Melissa L Finucane et al.•European Journal of Operational…•2007

  • Is the Replicability Crisis Overblown? Three Arguments Examined

    Open Access•Harold Pashler, Christine R Harris•Perspectives on Psychological…•2012

  • General Performance on a Numeracy Scale among Highly Educated Samples

    Open Access•Isaac M Lipkus, Isaac Lipkus et al.•Medical Decision Making•2001

  • Advances in prospect theory

    Open Access•Amos Tversky, Daniel Kahneman•Journal of Risk and Uncertainty•1992

  • Statistical mediation analysis with a multicategorical independent variable

    Open Access•Andrew F Hayes, Kristopher J Preacher•British Journal of Mathematical…•2014

  • Asymptotic and resampling strategies for assessing and comparing indirect effects in multiple mediator models

    Open Access•Kristopher J Preacher, Andrew F Hayes•Behavior Research Methods•2008

  • On the psychology of prediction.

    Daniel Kahneman, Amos Tversky•Psychological Review•1973

  • Risk Analysis and Human Behavior

    Baruch Fischhoff•Risk analysis and human behaviour•2013

  • Gender, race, and perceived risk

    Melissa L Finucane, Paul Slovic et al.•Health Risk & Society•2000

  • Are People Optimistically Biased about the Risk of Covid-19 Infection? Lessons from the First Wave of the Pandemic in Europe

    Open Access•Kathleen Mccoll, Marion Debin et al.•International Journal of…•2021

  • Are trivial risks the greatest risks of all

    Paul Slovic•Journal of Risk Research•1999

  • Scientist and public responses to BSE‐related risk

    Jocelyn Raude, Claude Fischler et al.•Journal of Risk Research•2005

  • Risk perceptions of Covid-19 around the world

    Open Access•Sarah Dryhurst, Claudia R Schneider et al.•Journal of Risk Research•2020

  • Feeling the Numbers

    Open Access•Darya Petrova, Dafina G Petrova et al.•Journal of Behavioral Decision…•2013

  • Do Smokers Underestimate Risks

    W Kip Viscusi•Journal of Political Economy•1990

  • Affect, generalization, and the perception of risk

    E Johnson, Amos Tversky•Journal of Personality and Social…•1983

  • How to Make Cognitive Illusions Disappear

    Gerd Gigerenzer•European Review of Social…•1991

  • Replicating patterns of prospect theory for decision under risk

    Open Access•Kai Ruggeri, Sonia Alí et al.•Nature Human Behaviour•2020

  • How numeracy influences risk comprehension and medical decision making

    Valerie F Reyna, Wendy L Nelson et al.•Psychological Bulletin•2009

Highly citedNo

Tools

Open DOIOpen Access
Ethnos_APP • Open Source Project • MIT License • Frontend v2.0.0 • Privacy and Cookies • API Documentation: api.ethnos.app/docs • API Source Code: GitHub • DOI: 10.5281/zenodo.17049435 • Frontend Source Code: GitHub • DOI: 10.5281/zenodo.17050053 • cruz.rio.br • Expectantes Misericordiae