We evaluated the degree to which delay to reinforcement and social distance concurrently influenced altruistic choices within a discounting paradigm. Forty participants completed two discounting tasks in a repeated measures design. In the SELF task, delay was parametrically imposed on the participant; in the OTHER task, delay was parametrically imposed on the hypothetical other. Results of a multilevel analysis of indifference data supported a hyperbolic discount rate for social distance in both conditions and delay in the OTHER condition. Results also suggested a statistically significant difference in the discount rate between the two discounting tasks (t = -4.53, p < .001 and t = -4.03, p < .001, respectively). Due to a poor fit of the hyperbolic delay discount rate for the SELF task, we compared the hyperbolic fit to a logarithmic model that described an increase in subjective value as a function of delay to reinforcement for the participant. Given support of these models at the individual and group level, we developed multiplicative models for the SELF and OTHER tasks that provided strong fits for the obtained median indifference values. Results are discussed in terms of interpreting human behavior believed to be altruistic as well as potential implications for influencing social policy.

我们评估了减价范式中强化延迟和社交距离同时影响利他选择的程度。四十名参与者在重复测量设计中完成了两项折扣任务。在SELF任务中，参数化地将延迟强加给了参与者。在OTHER任务中，将参数上的延迟强加给假设的对方。对冷漠数据进行多级分析的结果支持两种情况下社交距离的双曲线折现率，以及其他条件下的延迟。结果还表明，两个贴现任务之间的贴现率在统计上有显着差异（t = -4.53，p <.001和t = -4.03，p分别<.001）。由于针对SELF任务的双曲线延迟折扣率拟合度较差，因此我们将双曲线拟合与对数模型进行了比较，该模型描述了主观价值的增加是参与者对强化的延迟的函数。鉴于这些模型在个人和小组级别的支持，我们为SELF和OTHER任务开发了乘法模型，这些模型为获得的中位数无差异值提供了强大的契合度。讨论结果的方式包括解释被认为是无私的人类行为以及对影响社会政策的潜在影响。