How to make a risk seem riskier: The ratio bias versus construal level theory

Abstract

Abstract Which statement conveys greater risk: “100 people die from cancer every day” or “36,500 people die from cancer every year”? In statistics where both frequencies and temporal information are used to convey risk, two theories predict opposite answers to this question. Construal level theory predicts that “100 people die from cancer every day” will be judged as more risky, while the ratio bias predicts that the equivalent “36,500 people die from cancer every year” will result in higher risk judgments. An experiment investigated which format produces higher risk ratings, and whether ratings are influenced by increasing the salience of the numerical or temporal part of the statistic. Forty-eight participants were randomly assigned to a numerical, temporal or control salience condition, and rated risk framed as number of deaths per day or per year. The year format was found to result in higher perceived risk, indicating that the ratio bias effect is dominant, but there was no effect of salience.

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