Some affective consequences of social comparison and reflection processes: The pain and pleasure of being close.

心理学 亲密度 情感(语言学) 相关性(法律) 任务(项目管理) 愉快 社会心理学 唤醒 认知心理学 面部表情 沟通 数学分析 数学 管理 神经科学 政治学 法学 经济
作者
Abraham Tesser,Murray G. Millar,Janet Moore
出处
期刊:Journal of Personality and Social Psychology [American Psychological Association]
卷期号:54 (1): 49-61 被引量:411
标识
DOI:10.1037//0022-3514.54.1.49
摘要

A self-evaluation maintenance (SEM) model of social behavior was described. According to the comparison process, when another outperforms the self on a task high in relevance to the self, the closer the other the greater the threat to self-evaluation. According to the reflection process, when another outperforms the self on a task low in relevance to the self, the closer the other the greater the promise of augmentation to self-evaluation. Affect was assumed to reflect threats and promises to self-evaluation. In three studies, subjects were given feedback about own performance and the performance of a close (friend) and distant (stranger) other on tasks that were either low in self-relevance (Study 2) or that varied in self-relevance (Studies 1 and 3). In Study 1 (N = 31), subjects' performance on simple and complex tasks after each feedback trial served as a measure of arousal. Being outperformed by a close other resulted in greater arousal than being outperformed by a distant other. In Study 2 (N = 30), evaluative ratings of words unrelated to task performance served as an indirect measure of affect. Results indicated that when relevance is low, more positive affect is associated with a friend's outperforming the self than either a friend's performing at a level equal to the self or being outperformed by a stranger. In Study 3 (N = 31), subjects received feedback while their facial expressions were monitored. Pleasantness of expression was an interactive function of relevance of task, relative performance, and closeness of comparison other. The results of all three studies were interpreted as being generally consistent with the SEM model.
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