Abstract
Human risky decision-making is known to be highly susceptible to profit-motivated responses elicited by the way in which options are framed. In fact, studies investigating the framing effect have shown that the choice between sure and risky options depends on how these options are presented. Interestingly, the probability of gain of the risky option has been highlighted as one of the main factors causing variations in susceptibility to the framing effect. However, while it has been shown that high probabilities of gain of the risky option systematically lead to framing bias, questions remain about the influence of low probabilities of gain. Therefore, the first aim of this paper was to clarify the respective roles of high and low probabilities of gain in the framing effect. Due to the difference between studies using a within- or between-subjects design, we conducted a first study investigating the respective roles of these designs. For both designs, we showed that trials with a high probability of gain led to the framing effect whereas those with a low probability did not. Second, as emotions are known to play a key role in the framing effect, we sought to determine whether they are responsible for such a debiasing effect of the low probability of gain. Our second study thus investigated the relationship between emotion and the framing effect depending on high and low probabilities. Our results revealed that positive emotion was related to risk-seeking in the loss frame, but only for trials with a high probability of gain. Taken together, these results support the interpretation that low probabilities of gain suppress the framing effect because they prevent the positive emotion of gain anticipation.
Highlights
Choosing between several options is a major challenge in our everyday lives
A significant main effect of Frame revealed that participants were overall susceptible to the framing effect [F(1,92) = 5.60; p < 0.05; η2p = 0.06], in that they made more risky choices in the loss frame (M ± SD; MLoss = 60% ± 49) than in the gain frame (MGain = 38% ± 49)
A significant interaction was found between Frame and Probability of gain [F(1,92) = 7.82; p < 0.01; η2p = 0.08], indicating that participants demonstrated a framing effect in the high probability condition (p < 0.01; MLoss = 79% ± 41; MGain = 29% ± 46; η2p = 0.25) but not in the low probability condition (p > 0.95; MLoss = 42% ± 50; MGain = 46% ± 51)
Summary
As we operate with limited resources, our decisions systematically require an evaluation of energy costs and potential rewards (Rangel et al, 2008) This evaluation enables us to select options that minimize costs and maximize benefits, i.e., leading to the best outcomes in terms of biological fitness. Type 1 processing operates quickly, is effortless, independent of working memory and cognitive ability. Everyday mental activities, such as knowing that 2+2 = 4 or thinking of London when the capital of Great Britain is mentioned, are some examples of the automatic activities that are attributed to Type 1 thinking. Type 2 processing is relatively slow, effortful, heavily dependent on working memory and related to individual differences in cognitive ability (Evans, 2011). Because Type 1 is fast, errors of intuitive thought are often difficult to prevent and cannot be always filtered by Type 2
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