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Psychologists have long been interested in studying individual differences in implicit motives. Implicit motives are typically measured asking respondents to write fantasy-stories based on a series of pictures showing one or several persons. The stories are then coded for implicit motivational content by trained experts because researchers have long assumed that respondents have no conscious access to the motivational themes in the stories they write. However, empirical research on self-evaluation of implicit motives is scarce. In this article, we provide new insights into this topic with a new measurement procedure—the motive self-categorization (MSC) test. In the MSC, respondents first fill out an implicit motive measure and then self-code their stories using lists of picture-specific statements that are typical concrete manifestations of implicit motives in the specific picture. We studied the MSC in a sample of 247 respondents by analyzing convergence with expert codings using a latent multitrait–multimethod item response theory (IRT) model. Results showed respondents could evaluate the motivational content of their stories (latent motive–motive rs = .37–.62), IRT latent motive scores based on self-categorization showed evidence of reliability (rs = .42–.67), and we found small method effects. The discussion focuses on implications for theory on measuring implicit motives and the possibility that self-insight occasionally goes beyond expert insight. (PsycINFO Database Record (c) 2019 APA, all rights reserved)





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