ISSN 0439-755X
CN 11-1911/B
主办:中国心理学会
   中国科学院心理研究所
出版:科学出版社

心理学报 ›› 2017, Vol. 49 ›› Issue (12): 1537-1547.doi: 10.3724/SP.J.1041.2017.01537

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 调节定向和调节匹配对情感预测中 影响偏差的影响

 耿晓伟; 姜宏艺   

  1.  (鲁东大学教育科学学院, 烟台 264011)
  • 收稿日期:2016-10-17 出版日期:2017-12-25 发布日期:2017-10-25
  • 通讯作者: 耿晓伟, E-mail: fengandwei@126.com E-mail:
  • 基金资助:
     国家自然科学基金项目(71401068), 教育部人文社科项目(14YJCZH036)资助。

 Influence of regulatory focus and regulatory fit on impact biases in affective forecast

 GENG Xiaowei; JIANG Hongyi   

  1.  (School of Education Science, Ludong University, Yantai 264011, China)
  • Received:2016-10-17 Online:2017-12-25 Published:2017-10-25
  • Contact: GENG Xiaowei, E-mail: fengandwei@126.com E-mail:
  • Supported by:
     

摘要:   现实生活中, 人们在决策前需要对决策可能带来的结果进行预测。人们往往会高估未来事件对其情绪的影响, 这被称为影响偏差。本研究从自我调节理论的视角出发, 考察了调节定向和调节匹配对情感预测中影响偏差的影响。实验1和实验2分别在积极和消极情景中考察了调节定向对情感预测偏差的影响; 实验3和实验4分别在消极和积极情景中考察了调节匹配对情感预测偏差的影响。结果发现:(1)在对积极情感的预测中, 促进定向个体比防御定向个体出现更大的影响偏差; 在对消极情感的预测中, 防御定向个体比促进定向个体出现更大的影响偏差。(2)调节匹配比调节不匹配条件下, 个体会出现更大的影响偏差。因此, 情感预测中的影响偏差是个体实现目标的一种自我调节策略, 会受到调节定向和调节匹配的影响。

关键词: 调节定向, 调节匹配, 情感预测, 影响偏差

Abstract:  Our minor and major decision are often dependent on our predictions of how pleasant or unpleasant these events would make us feel, that is, our affective forecasts (Wilson & Gilbert, 2003). People overestimate the intensity and duration of their affective reactions to the event in focus, which is called the impact bias (Wilson & Gilbert, 2003). Most previous studies have focused on the cognitive sources of impact bias and the individual differences in impact bias. However, few studies have shed light on the motivated underpinnings of impact bias. The present research examined people’s overestimation of the hedonic impact of future events as a form of self -regulation. That is, sometimes people use impact bias to motivate themselves to actualize their goals. Thus, based on the self-regulatory theory, this study aimed to explore the effects of regulatory focus and regulatory fit on the impact biases. The hypotheses were: (i) in forecasting positive affect, individuals with promotive focus would show greater impact bias than those with preventive focus (H1a); (ii) in forecasting negative affect, individuals with preventive focus would show greater impact bias than those with promotive focus (H1b); (iii) regulatory fit would induce impact bias (H2). In Experiment 1, we examined the influences of regulatory focus on impact biases in forecasting positive affect. A total of 61 undergraduates were randomly divided into 2 conditions, specifically, promotive focus priming and preventive focus priming. They were then asked to finish a discriminability test. Before the test, they predicted the happiness of success in the test. After the test, they were told that they had succeeded in the test, and were asked to report their actual happiness of success in the test. Independent-sample t-test showed that participants with promotive focus overestimated the pleasant of success in discriminability test more than those with preventive focus. In Experiment 2, we tested the influences of regulatory focus on impact biases in forecasting negative affect. Participants’ predominant predisposition for a promotion or prevention state was measured first before they performed a memory task. Before the task, they predicted how happy they would be after a failure in the test. Then, they were told that they failed in the memory test and were asked to evaluate how happy they were. Independent-sample t-test showed that participants with preventive focus overestimated the unhappiness of failure in memory test more than those with promotive focus. In Experiment 3, we tested the influence of regulatory fit on impact biases in forecasting negative affect by 2 (Regulatory focus: promotion vs prevention) × 2 (Strategy: eagerness vs vigilance) between-subject design. A total of 120 undergraduates were randomly divided into 4 groups and were asked to finish a memory test. Before the test, they predicted the unhappiness of failure in the test. After the test, they were told that they had failed in the test, and were asked to report their actual unhappiness of the failure in the test. The results showed that participants overestimate the unhappiness of failure in memory test in the condition of regulatory fit more than in the regulatory non-fit condition. In Experiment 4, we tested the effect of regulatory fit on impact bias in forecasting positive affect. A total of 128 undergraduates were randomly divided into 4 groups and were asked to finish a finding differences test. Before the test, they predicted how happy they would be after the success in the test. After the test, they were told that they had succeeded in the test, and were asked to report their actual happiness of the success. The results showed that participants overestimate the happiness in the condition of regulatory fit more than regulatory non-fit condition. The present research investigated the motivated underpinning of impact bias based under the theory of self-regulatory, which helps our further understanding of the mechanism of impact bias. In addition, it can also help us to manage the improvement of the work engagement of employees. Limitations and further research have been discussed as well.

Key words: regulatory focus, regulatory fit, affective forecast, impact bias

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