Unraveling the three faces of self-esteem: A new information-processing sociometer perspective

Based on an integration of sociometer theory and information-processing models, the present study investigated the predictive validity of three self-esteem measures: self-report, an implicit association test, and an affective priming task. In a first session, self-esteem measures were obtained from 93 participants. After an interval of four weeks, interpersonal perception ratings were collected in small round-robin groups. Participants were requested to briefly introduce themselves to the group before evaluating one another and indicating how they expected to be evaluated by the others (metaperceptions). As hypothesized, all three self-esteem measures independently predicted the perception of being valued (PBV) in a real-life situation. In sum, the present study supports the idea that three independent faces of self-esteem can fruitfully be distinguished.