"1-in-X" bias: "1-in-X" format causes overestimation of health-related risks

J Exp Psychol Appl. 2018 Dec;24(4):431-439. doi: 10.1037/xap0000190. Epub 2018 Sep 24.

Abstract

According to the "1-in-X" effect, "1-in-X" ratios (e.g., 1 in 12) trigger a higher subjective probability than do numerically equivalent "N-in-X*N" ratios (e.g., 3 in 36). Here we tested the following: (a) the effect on objective measures, (b) its consequences for decision-making, (c) whether this effect is a form of bias by measuring probability accuracy, and (d) its amplification in people with lower health literacy and numeracy. In parallel-designed experiments, 975 participants from the general adult population participated in 1 of 5 experiments following a 2(format: "1-in-X" or "N-in-X*N") × 4(scenarios) mixed design. Participants assessed the risk of contracting a disease on either a verbal probability scale (Experiment 1) or a numerical probability/frequency scale with immediate (Experiments 2-3) or delayed presentation (Experiments 4-5). Participants also made a health-related decision and completed a health literacy and numeracy scale. The "1-in-X" ratios yielded higher probability perceptions than did the "N-in-X*N" ratios and affected relevant decisions. Critically, the "1-in-X" ratios led to a larger objective overestimation of numerical probabilities than did the "N-in-X*N" ratios. People with lower levels of health literacy and numeracy were not more sensitive to the bias. Health professionals should use "1-in-X" ratios with great caution when communicating to patients, because they overestimate health risks. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

MeSH terms

  • Adolescent
  • Adult
  • Aged
  • Communication*
  • Decision Making*
  • Female
  • Health Literacy*
  • Humans
  • Male
  • Middle Aged
  • Probability
  • Risk Assessment
  • Young Adult

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