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Improving Public Interpretation of Probabilistic Test Results: Distributive Evaluations

Abstract : Health service users err in posttest probability evaluations. Here we document for the first time that users succeed when they reason about numbers of cases and make distributive evaluations. A sample of women interested in prenatal testing incorrectly evaluated the posttest probability that a given fetus had an anomaly, but regardless of their numeracy level, they correctly apportioned the cases for and against that hypothesis. This finding shows that health service users are not doomed to fail in dealing with single-case probabilities and suggests that probabilistic data can be used effectively for communicating test results.
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Contributor : Jean-Baptiste Melmi Connect in order to contact the contributor
Submitted on : Wednesday, January 11, 2017 - 4:59:15 PM
Last modification on : Tuesday, October 19, 2021 - 10:58:52 PM




Stefania Pighin, Michel Gonzalez, Lucia Savadori, Vittorio Girotto. Improving Public Interpretation of Probabilistic Test Results: Distributive Evaluations. Medical Decision Making, SAGE Publications, 2015, 35 (1), pp.12-15. ⟨10.1177/0272989X14536268⟩. ⟨hal-01432424⟩



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