Personality and its Impacts across the Behavioral Sciences: A Quantitative Review of Meta-Analytic Findings

Abstract

Personality has consequences. Following the emergence of and scholarly convergence around the Five-Factor Model (FFM), or Big Five, some 35 years ago, research interest in personality traits has exploded across the behavioral sciences. Meta-analyses reporting Big Five (i.e., Emotional Stability, Agreeableness, Conscientiousness, Extraversion, and Openness/Intellect) relations have so proliferated that a quantitative second-order review was needed. The purpose of this dissertation was to conduct such a review. Data were gathered from an exhaustive search (through July 2016) of 167 published Big Five meta-analyses, which reported empirical relations to 712 unique correlate, behavioral, and outcome variables. A multi-hurdle selection process was used to screen variables for study inclusion, and a content-based coding procedure was used to organize variables into a set of four theoretically meaningful “meta-categories”—Well-Being, Performance, Leadership, and Counterproductivity—which were examined in series of three studies. Study 1 used procedures from first-order and second-order psychometric meta-analysis to estimate univariate relations for the Big Five traits. Empirical effect size benchmarks for interpreting trait relations were also developed. Study 2 built on the prior study by estimating univariate relations for the two metatraits, Stability and Plasticity. Results represent the most comprehensive nomological network of metatrait relations in the literature, and provide evidence of their wide-ranging theoretical and empirical relevance (e.g., Stability was the strongest predictor of Counterproductivity variables, and Plasticity was the strongest predictor of Leadership variables). Finally, Study 3 examined multivariate effects of both Big Five and metatraits models. Dominance analysis was also used to examine traits’ relative contribution to overall prediction. Results indicate that both trait models contributed substantial variance to predicting variables that are consequential and fundamental to human interest, and that most of these variables were multiply determined by at least two or three traits. Together, these studies summarize and advance knowledge about personality and its impacts across the behavioral sciences.