Emotional reactions are an important element in the motivation to help others. Our research examined the role of affective vs. deliberative information processing in the genesis and use of emotional reactions in decisions to provide financial aid to people in distress. In two studies, we investigated whether information processing mode influenced participants' donations, affective reactions, and the relationship between the two. Information processing was manipulated by a priming procedure and a cognitive load paradigm. Participants' empathic emotions were assessed by self-reported sympathy, compassion, and distress. Additionally, we measured how much better a donation would make participants feel and their anticipated regret for not donating, which were taken as indicators of their motivation to donate as a form of mood management. Results suggest that different mechanisms govern the initial decision to donate money (Stage 1) compared to later decisions on how much money to donate (Stage 2). Motivations for mood management were primarily predictive of donation decisions, whereas empathic feelings were predictive of the donation amount. The potentially disruptive effects of deliberative processing on prosocial behavior are discussed in light of a twostage processing model of donations.

How we react to humanitarian crises, epidemics, and other tragic events involving the loss of human lives depends largely on the extent to which we are moved by the size of their associated death tolls. Many studies have demonstrated that people generally exhibit a diminishing sensitivity to the number of human fatalities and, equivalently, a preference for risky (vs. sure) alternatives in decisions under risk involving human losses. However, the reason for this tendency remains unknown. Here we show that the distributions of event-related death tolls that people observe govern their evaluations of, and risk preferences concerning, human fatalities. In particular, we show that our diminishing sensitivity to human fatalities follows from the fact that these death tolls are approximately power-law distributed. We further show that, by manipulating the distribution of mortality-related events that people observe, we can alter their risk preferences in decisions involving fatalities. Finally, we show that the tendency to be risk-seeking in mortality-related decisions is lower in countries in which high-mortality events are more frequently observed. Our results support a model of magnitude evaluation based on memory sampling and relative judgment. This model departs from the utility-based approaches typically encountered in psychology and economics in that it does not rely on stable, underlying value representations to explain valuation and choice, or on choice behavior to derive value functions. Instead, preferences concerning human fatalities emerge spontaneously from the distributions of sampled events and the relative nature of the evaluation process.decision-making ͉ psychophysics ͉ risk preferences ͉ value of human lives ͉ decision by sampling

No abstract

No abstract