Literature DB >> 19968421

The implications of Big Five standing for the distribution of trait manifestation in behavior: fifteen experience-sampling studies and a meta-analysis.

William Fleeson1, Patrick Gallagher.   

Abstract

One of the fundamental questions in personality psychology is whether and how strongly trait standing relates to the traits that people actually manifest in their behavior when faced with real pressures and real consequences of their actions. One reason this question is fundamental is the common belief that traits do not predict how individuals behave, which leads to the reasonable conclusion that traits are not important to study. However, this conclusion is surprising given that there is almost no data on the ability of traits to predict distributions of naturally occurring, representative behaviors of individuals (and that there are many studies showing that traits do indeed predict specific behaviors). The authors describe a meta-analysis of 15 experience-sampling studies, conducted over the course of 8 years, amassing over 20,000 reports of trait manifestation in behavior. Participants reported traits on typical self-report questionnaires, then described their current behavior multiple times per day for several days as the behavior was occurring. Results show that traits, contrary to expectations, were strongly predictive of individual differences in trait manifestation in behavior, predicting average levels with correlations between .42 and .56 (approaching .60 for stringently restricted studies). Several other ways of summarizing trait manifestation in behavior were also predicted from traits. These studies provide evidence that traits are powerful predictors of actual manifestation of traits in behavior.

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Year:  2009        PMID: 19968421      PMCID: PMC2791901          DOI: 10.1037/a0016786

Source DB:  PubMed          Journal:  J Pers Soc Psychol        ISSN: 0022-3514


  21 in total

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  43 in total

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9.  Are traits useful? Explaining trait manifestations as tools in the pursuit of goals.

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10.  Planned missing-data designs in experience-sampling research: Monte Carlo simulations of efficient designs for assessing within-person constructs.

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