6 research outputs found

    Doing Despite Disliking: Self‐regulatory Strategies in Everyday Aversive Activitie

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    We investigated the self‐regulatory strategies people spontaneously use in their everyday lives to regulate their persistence during aversive activities. In pilot studies (pooled N = 794), we identified self‐regulatory strategies from self‐reports and generated hypotheses about individual differences in trait self‐control predicting their use. Next, deploying ambulatory assessment (N = 264, 1940 reports of aversive/challenging activities), we investigated predictors of the strategies' self‐reported use and effectiveness (trait self‐control and demand types). The popularity of strategies varied across demands. In addition, people higher in trait self‐control were more likely to focus on the positive consequences of a given activity, set goals, and use emotion regulation. Focusing on positive consequences, focusing on negative consequences (of not performing the activity), thinking of the near finish, and emotion regulation increased perceived self‐regulatory success across demands, whereas distracting oneself from the aversive activity decreased it. None of these strategies, however, accounted for the beneficial effects of trait self‐control on perceived self‐regulatory success. Hence, trait self‐control and strategy use appear to represent separate routes to good self‐regulation. By considering trait‐ and process‐approaches these findings promote a more comprehensive understanding of self‐regulatory success and failure during people's daily attempts to regulate their persistence

    Task Enjoyment as an Individual Difference Construct

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    Are there individual differences in the tendency to enjoy tasks regardless of the tasks' contents or situational determinants? To answer this question, we constructed and validated the six-item Trait Task Enjoyment Scale (TTES). In Study 1, it had an internally consistent one-factor structure (pooled N = 997); good test-retest reliabilities over 1 and 4 months; measurement invariance regarding gender (strong) and time (partial strong); and was not redundant with respect to a large number of theoretically related constructs. In Studies 2 and 3, the TTES predicted self-reported momentary task enjoyment, one of its opposites, boredom, and voluntary persistence in a free-choice paradigm. It did so for various tasks, including thirty diverse tasks presented in vignettes and a memory task in the lab. Results suggest that the TTES may predict momentary task enjoyment regardless of objective task aversiveness or, in this case, equally well for tasks with boring or enjoyable contents. The TTES addresses an important gap in current research on task enjoyment and is an adequately valid and reliable research tool

    Measuring Implicit Motives with the Picture Story Exercise (PSE): Databases of Expert-Coded German Stories, Pictures, and Updated Picture Norms

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    We present two openly accessible databases related to the assessment of implicit motives using Picture Story Exercises (PSEs): (a) A database of 183,415 German sentences, nested in 26,389 stories provided by 4,570 participants, which have been coded by experts using Winter's coding system for the implicit affiliation/intimacy, achievement, and power motives, and (b) a database of 54 classic and new pictures which have been used as PSE stimuli. Updated picture norms are provided which can be used to select appropriate pictures for PSE applications. Based on an analysis of the relations between raw motive scores, word count, and sentence count, we give recommendations on how to control motive scores for story length, and validate the recommendation with a meta-analysis on gender differences in the implicit affiliation motive that replicates existing findings. We discuss to what extent the guiding principles of the story length correction can be generalized to other content coding systems for narrative material. Several potential applications of the databases are discussed, including (un)supervised machine learning of text content, psychometrics, and better reproducibility of PSE research
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