Oganian Yulia, Heekeren Hauke R, Korn Christoph W
1 Department of Education and Psychology, Freie Universität Berlin, Berlin, Germany.
2 Bernstein Center for Computational Neuroscience Berlin, Berlin, Germany.
Q J Exp Psychol (Hove). 2019 Jan;72(1):60-75. doi: 10.1177/1747021818774789. Epub 2018 May 22.
Optimistic estimates about the personal future constitute one of the best-described and most-debated decision biases related to emotion. Nevertheless, it has been difficult to isolate manipulations that reduce optimistic estimates. Eliciting estimates in a foreign language is a promising candidate manipulation because foreign language use alters decision biases in scenarios with emotional components. Consequently, we tested whether foreign language use reduces optimistic estimates. In a laboratory experiment, participants ( n = 45) estimated their probability of experiencing life events either in their native language or a foreign language, in which they were highly proficient. We found no differences in these estimates or in the updating of these estimates after receiving feedback about the population baseline probability. Importantly, three online experiments with large sample sizes ( ns = 706, 530, and 473) showed that using a foreign language with low proficiency reduced comparative optimism. Participants in the online experiments had diverse proficiency levels and were matched on a variety of control metrics. Fine-grained analyses indicated that low proficiency weakens the coupling between probability estimates and rated arousal. Overall, our findings suggest that an important decision bias can be reduced when using a foreign language with low proficiency.
对个人未来的乐观估计是与情绪相关的描述最为详尽且争议最大的决策偏差之一。然而,一直以来都很难找到能够减少乐观估计的操控方法。以外语进行估计是一种很有前景的候选操控方式,因为使用外语会改变具有情感成分的情景中的决策偏差。因此,我们测试了使用外语是否会减少乐观估计。在一项实验室实验中,45名参与者用母语或他们熟练掌握的外语估计自己经历生活事件的概率。在收到关于总体基线概率的反馈后,我们发现这些估计值以及这些估计值的更新没有差异。重要的是,三项大样本量的在线实验(样本量分别为706、530和473)表明,使用不熟练的外语会降低比较性乐观情绪。在线实验中的参与者有不同的熟练程度,并在各种控制指标上进行了匹配。细粒度分析表明,不熟练会削弱概率估计与评定的唤醒之间的耦合。总体而言,我们的研究结果表明,使用不熟练的外语时,一种重要的决策偏差可以得到减少。