Clay Summer N, Clithero John A, Harris Alison M, Reed Catherine L
Department of Behavioral and Organizational Sciences, Claremont Graduate University, Claremont, CA, United States.
Department of Economics, Pomona College, Claremont, CA, United States.
Front Psychol. 2017 Oct 10;8:1708. doi: 10.3389/fpsyg.2017.01708. eCollection 2017.
Defined as increased sensitivity to losses, loss aversion is often conceptualized as a cognitive bias. However, findings that loss aversion has an attentional or emotional regulation component suggest that it may instead reflect differences in information processing. To distinguish these alternatives, we applied the drift-diffusion model (DDM) to choice and response time (RT) data in a card gambling task with unknown risk distributions. Loss aversion was measured separately for each participant. Dividing the participants into terciles based on loss aversion estimates, we found that the most loss-averse group showed a significantly lower drift rate than the other two groups, indicating overall slower uptake of information. In contrast, neither the starting bias nor the threshold separation (barrier) varied by group, suggesting that decision thresholds are not affected by loss aversion. These results shed new light on the cognitive mechanisms underlying loss aversion, consistent with an account based on information accumulation.
损失厌恶被定义为对损失的敏感性增加，它通常被概念化为一种认知偏差。然而，有研究发现损失厌恶具有注意力或情绪调节成分，这表明它可能反而反映了信息处理方面的差异。为了区分这些可能性，我们将漂移扩散模型（DDM）应用于风险分布未知的纸牌赌博任务中的选择和反应时间（RT）数据。对每个参与者分别测量损失厌恶程度。根据损失厌恶估计值将参与者分为三组，我们发现最厌恶损失的组的漂移率明显低于其他两组，这表明总体信息获取速度较慢。相比之下，起始偏差和阈值分离（屏障）在各组之间均无差异，这表明决策阈值不受损失厌恶的影响。这些结果为损失厌恶背后的认知机制提供了新的线索，与基于信息积累的解释一致。
