Wändi Bruine de Bruin1, Katherine G Carman2. 1. Departments of Social and Decision Sciences and of Engineering and Public Policy, Carnegie Mellon University, Pittsburgh, Pennsylvania (WBB) 2. Department of Economics, Tilburg University, Tilburg, the Netherlands (KGC)
Abstract
OBJECTIVES: Risk perceptions are central to good health decisions. People can judge valid probabilities but use 50% disproportionately. The authors hypothesized that 50% is more likely than other responses to reflect not knowing the probability, especially among individuals with low education and numeracy, and evaluated the usefulness of eliciting "don't know" explanations. METHODS: Respondents (n = 1020) judged probabilities for living or dying in the next 10 years, indicating whether they gave a good estimate or did not know the chances. They completed demographics, medical history, and numeracy questions. RESULTS: Overall, 50% was more likely than other probabilities to be explained as "don't know" (v. "a good estimate"). Correlations of using 50% with low education and numeracy were mediated by expressing "don't know." Judged probabilities for survival and mortality explained as "don't know" had lower correlations with age, diseases, and specialist visits. CONCLUSIONS: When judging risks, 50% may reflect not knowing the probability, especially among individuals with low numeracy and education. Probabilities expressed as "don't know" are less valid. Eliciting uncertainty could benefit theoretical models and educational efforts.
OBJECTIVES: Risk perceptions are central to good health decisions. People can judge valid probabilities but use 50% disproportionately. The authors hypothesized that 50% is more likely than other responses to reflect not knowing the probability, especially among individuals with low education and numeracy, and evaluated the usefulness of eliciting "don't know" explanations. METHODS: Respondents (n = 1020) judged probabilities for living or dying in the next 10 years, indicating whether they gave a good estimate or did not know the chances. They completed demographics, medical history, and numeracy questions. RESULTS: Overall, 50% was more likely than other probabilities to be explained as "don't know" (v. "a good estimate"). Correlations of using 50% with low education and numeracy were mediated by expressing "don't know." Judged probabilities for survival and mortality explained as "don't know" had lower correlations with age, diseases, and specialist visits. CONCLUSIONS: When judging risks, 50% may reflect not knowing the probability, especially among individuals with low numeracy and education. Probabilities expressed as "don't know" are less valid. Eliciting uncertainty could benefit theoretical models and educational efforts.
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Authors: Wändi Bruine de Bruin; Annika Wallin; Andrew M Parker; JoNell Strough; Janel Hanmer Journal: Med Decis Making Date: 2017-05-05 Impact factor: 2.583