Meta-analytic relations between personality and cognitive ability.

Cognitive ability and personality are fundamental domains of human psychology. Despite a century of vast research, most ability-personality relations remain unestablished. Using contemporary hierarchical personality and cognitive abilities frameworks, we meta-analyze unexamined links between personality traits and cognitive abilities and offer large-scale evidence of their relations. This research quantitatively summarizes 60,690 relations between 79 personality and 97 cognitive ability constructs in 3,543 meta-analyses based on data from millions of individuals. Sets of novel relations are illuminated by distinguishing hierarchical personality and ability constructs (e.g., factors, aspects, facets). The links between personality traits and cognitive abilities are not limited to openness and its components. Some aspects and facets of neuroticism, extraversion, and conscientiousness are also considerably related to primary as well as specific abilities. Overall, the results provide an encyclopedic quantification of what is currently known about personality-ability relations, identify previously unrecognized trait pairings, and reveal knowledge gaps. The meta-analytic findings are visualized in an interactive webtool. The database of coded studies and relations is offered to the scientific community to further advance research, understanding, and applications.

Using natural language processing and machine learning to replace human content coders.

Content analysis is a common and flexible technique to quantify and make sense of qualitative data in psychological research. However, the practical implementation of content analysis is extremely labor-intensive and subject to human coder errors. Applying natural language processing (NLP) techniques can help address these limitations. We explain and illustrate these techniques to psychological researchers. For this purpose, we first present a study exploring the creation of psychometrically meaningful predictions of human content codes. Using an existing database of human content codes, we build an NLP algorithm to validly predict those codes, at generally acceptable standards. We then conduct a Monte-Carlo simulation to model how four dataset characteristics (i.e., sample size, unlabeled proportion of cases, classification base rate, and human coder reliability) influence content classification performance. The simulation indicated that the influence of sample size and unlabeled proportion on model classification performance tended to be curvilinear. In addition, base rate and human coder reliability had a strong effect on classification performance. Finally, using these results, we offer practical recommendations to psychologists on the necessary dataset characteristics to achieve valid prediction of content codes to guide researchers on the use of NLP models to replace human coders in content analysis research. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Agreeableness and Its Consequences: A Quantitative Review of Meta-Analytic Findings.

Agreeableness impacts people and real-world outcomes. In the most comprehensive quantitative review to date, we summarize results from 142 meta-analyses reporting effects for 275 variables, which represent N > 1.9 million participants from k > 3,900 studies. Arranging variables by their content and type, we use an organizational framework of 16 conceptual categories that presents a detailed account of Agreeableness' external relations. Overall, the trait has effects in a desirable direction for 93% of variables (grand mean ρ¯M=.16). We also review lower order trait evidence for 42 variables from 20 meta-analyses. Using these empirical findings, in tandem with existing theory, we synthesize eight general themes that describe Agreeableness' characteristic functioning across variables: self-transcendence, contentment, relational investment, teamworking, work investment, lower results emphasis, social norm orientation, and social integration. We conclude by discussing potential boundary conditions of findings, contributions and limitations of our review, and future research directions.

WristPrint: Characterizing User Re-identification Risks from Wrist-worn Accelerometry Data.

Public release of wrist-worn motion sensor data is growing. They enable and accelerate research in developing new algorithms to passively track daily activities, resulting in improved health and wellness utilities of smartwatches and activity trackers. But, when combined with sensitive attribute inference attack and linkage attack via re-identification of the same user in multiple datasets, undisclosed sensitive attributes can be revealed to unintended organizations with potentially adverse consequences for unsuspecting data contributing users. To guide both users and data collecting researchers, we characterize the re-identification risks inherent in motion sensor data collected from wrist-worn devices in users' natural environment. For this purpose, we use an open-set formulation, train a deep learning architecture with a new loss function, and apply our model to a new data set consisting of 10 weeks of daily sensor wearing by 353 users. We find that re-identification risk increases with an increase in the activity intensity. On average, such risk is 96% for a user when sharing a full day of sensor data.

Meta-analytic criterion profile analysis.

Intraindividual patterns or configurations are intuitive explanations for phenomena, and popular in both lay and research contexts. Criterion profile analysis (CPA; Davison & Davenport, 2002) is a well-established, regression-based pattern matching procedure that identifies a pattern of predictors that optimally relate to a criterion of interest and quantifies the strength of that association. Existing CPA methods require individual-level data, limiting opportunities for reanalysis of published work, including research synthesis via meta-analysis and associated corrections for psychometric artifacts. In this article, we develop methods for meta-analytic criterion profile analysis (MACPA), including new methods for estimating cross-validity and fungibility of criterion patterns. We also review key methodological considerations for applying MACPA, including homogeneity of studies in meta-analyses, corrections for statistical artifacts, and second-order sampling error. Finally, we present example applications of MACPA to published meta-analyses from organizational, educational, personality, and clinical psychological literatures. R code implementing these methods is provided in the configural package, available at https://cran.r-project.org/package=configural and at https://doi.org/10.17605/osf.io/aqmpc. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

Meta-analytic five-factor model personality intercorrelations: Eeny, meeny, miney, moe, how, which, why, and where to go.

Meta-analysis is frequently combined with multiple regression or path analysis to examine how the Big Five/Five-Factor Model (FFM) personality traits relate to work outcomes. A common approach in such studies is to construct a synthetic correlation matrix by combining new meta-analyses of FFM-criterion correlations with previously published meta-analytic FFM intercorrelations. Many meta-analytic FFM intercorrelation matrices exist in the literature, with 3 matrices being frequently used in industrial-organizational (I-O) psychology and related fields (i.e., Mount, Barrick, Scullen, & Rounds, 2005; Ones, 1993; van der Linden, te Nijenhuis, & Bakker, 2010). However, it is unknown how the choice of FFM matrix influences study conclusions, why we observe such differences in the matrices, and which matrix researchers and practitioners should use for their specific studies. We conducted 3 studies to answer these questions. In Study 1, we demonstrate that researchers' choice of FFM matrix can substantively alter conclusions from meta-analytic regressions or path analyses. In Study 2, we present a new meta-analysis of FFM intercorrelations using measures explicitly constructed around the FFM and based on employee samples. In Study 3, we systematically explore the sources of differences in FFM intercorrelations using second-order meta-analyses of 44 meta-analytic FFM matrices. We find that personality rating source (self vs. other) and inventory-specific substantive and methodological features are the primary moderators of meta-analytic FFM intercorrelations. Based on the findings from these studies, we provide a framework to guide future researchers in choosing a meta-analytic FFM matrix that is most appropriate for their specific studies, research questions, and contexts. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

A century of research on conscientiousness at work.

Evidence from more than 100 y of research indicates that conscientiousness (C) is the most potent noncognitive construct for occupational performance. However, questions remain about the magnitudes of its effect sizes across occupational variables, its defining characteristics and functions in occupational settings, and potential moderators of its performance relation. Drawing on 92 unique meta-analyses reporting effects for 175 distinct variables, which represent n > 1.1 million participants across k > 2,500 studies, we present the most comprehensive, quantitative review and synthesis of the occupational effects of C available in the literature. Results show C has effects in a desirable direction for 98% of variables and a grand mean of [Formula: see text] (SD = 0.13), indicative of a potent, pervasive influence across occupational variables. Using the top 33% of effect sizes [Formula: see text] we synthesize 10 characteristic themes of C's occupational functioning: 1) motivation for goal-directed performance, 2) preference for more predictable environments, 3) interpersonal responsibility for shared goals, 4) commitment, 5) perseverance, 6) self-regulatory restraint to avoid counterproductivity, and 7) proficient performance-especially for 8) conventional goals, 9) requiring persistence. Finally, we examine C's relation to performance across 8 occupations. Results indicate that occupational complexity moderates this relation. That is, 10) high occupational complexity versus low-to-moderate occupational complexity attenuates the performance effect of C. Altogether, results suggest that goal-directed performance is fundamental to C and that motivational engagement, behavioral restraint, and environmental predictability influence its optimal occupational expression. We conclude by discussing applied and policy implications of our findings.

Extraversion advantages at work: A quantitative review and synthesis of the meta-analytic evidence.

How and to what extent does extraversion relate to work relevant variables across the lifespan? In the most extensive quantitative review to date, we summarize results from 97 published meta-analyses reporting relations of extraversion to 165 distinct work relevant variables, as well as relations of extraversion's lower order traits to 58 variables. We first update all effects using a common set of statistical corrections and, when possible, combine independent estimates using second-order meta-analysis (Schmidt & Oh, 2013). We then organize effects within a framework of four career domains-education, job application, on the job, and career/lifespan-and five conceptual categories: motivations, values, and interests; attitudes and well-being; interpersonal; performance; and counterproductivity. Overall, extraversion shows effects in a desirable direction for 90% of variables (grand mean ρ̄ = .14), indicative of a small, persistent advantage at work. Findings also show areas with more substantial effects (ρ̄ ≥ .20), which we synthesize into four extraversion advantages. These motivational, emotional, interpersonal, and performance advantages offer a concise account of extraversion's relations and a new lens for understanding its effects at work. Our review of the lower order trait evidence reveals diverse relations (e.g., the positive emotions facet has consistently advantageous effects, the sociability facet confers few benefits, the sensation-seeking facet is largely disadvantageous), and extends knowledge about the functioning of extraversion and its advantages. We conclude by discussing potential boundary conditions of findings, contributions and limitations of our review, and new research directions for extraversion at work. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

Direct and conceptual replications of the taxometric analysis of type a behavior.

We present direct and conceptual replications of the influential taxometric analysis of Type A Behavior (TAB; Strube, 1989), which reported evidence for the latent typology of the construct. Study 1, the direct replication (N = 2,373), duplicated sampling and methodological procedures of the original study, but results showed that the item indicators used in the original study lacked sufficient validity to unambiguously determine latent structure. Using improved factorial subscale indicators to further test the question, multiple taxometric procedures, in combination with parallel analyses of simulated data, failed to replicate the original typological finding. Study 2, the conceptual replication, tested the latent structure of the wider construct of TAB using the sample from the Caerphilly Prospective Study (N = 2,254), which contains responses to the three most widely used self-report measures of TAB: the Jenkins Activity Survey, Bortner scale, and Framingham scale. Factorial subscale indicators were derived from the measures and submitted to multiple taxometric procedures. Results of Study 2 converged with those of Study 1, providing clear evidence of latent dimensional structure. Overall, results suggest there is no evidence for the type in TAB. Findings imply that theoretical models of TAB, assessment practices, and data analytic procedures that assume a typology should be replaced by dimensional models, factorial subscale measures, and corresponding statistical approaches. Specific subscale measures that tap multiple Big Five trait domains, and show evidence of predictive utility, are also recommended. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

Are genetic and environmental influences on job satisfaction stable over time? A three-wave longitudinal twin study.

Job satisfaction research has unfolded as an exemplary manifestation of the "person versus environment" debate in applied psychology. With the increasing recognition of the importance of time, it is informative to examine a question critical to the dispositional view of job satisfaction: Are genetic influences on job satisfaction stable across different time points? Drawing upon dispositional and situational perspectives on job satisfaction and recent research in developmental behavioral genetics, we examined whether the relative potency of genetic (i.e., the person) and environmental influences on job satisfaction changed over time in a 3-wave longitudinal twin study. Biometric behavioral genetics analyses showed that genetic influences accounted for 31.2% of the variance in job satisfaction measured at approximately Age 21, which was markedly greater than the 18.7% and 19.8% of variance explained by genetic factors at Age 25 and Age 30. Such genetic influences were mediated via positive affectivity and negative affectivity, but not via general mental ability. After partialing out genetic influences, environmental influences on job satisfaction were related to interpersonal conflict at work and occupational status, and these influences were relatively stable across the 3 time points. These results offer important implications for organizations and employees to better understand and implement practices to enhance job satisfaction. (PsycINFO Database Record

Age and Employee Green Behaviors: A Meta-Analysis.

Recent economic and societal developments have led to an increasing emphasis on organizational environmental performance. At the same time, demographic trends are resulting in increasingly aging labor forces in many industrialized nations. Commonly held stereotypes suggest that older workers are less likely to be environmentally responsible than younger workers. To evaluate the degree to which such age differences are present, we meta-analyzed 132 independent correlations and 336 d-values based on 4676 professional workers from 22 samples in 11 countries. Contrary to popular stereotypes, age showed small positive relationships with pro-environmental behaviors, suggesting that older adults engaged in these workplace behaviors slightly more frequently. Relationships with age appeared to be linear for overall, Conserving, Avoiding Harm, and Taking Initiative pro-environmental behaviors, but non-linear trends were observed for Transforming and Influencing Others behaviors.

Cognitive predictors and age-based adverse impact among business executives.

Age differences on measures of general mental ability and specific cognitive abilities were examined in 2 samples of job applicants to executive positions as well as a mix of executive/nonexecutive positions to determine which predictors might lead to age-based adverse impact in making selection and advancement decisions. Generalizability of the pattern of findings was also investigated in 2 samples from the general adult population. Age was negatively related to general mental ability, with older executives scoring lower than younger executives. For specific ability components, the direction and magnitude of age differences depended on the specific ability in question. Older executives scored higher on verbal ability, a measure most often associated with crystallized intelligence. This finding generalized across samples examined in this study. Also, consistent with findings that fluid abilities decline with age, older executives scored somewhat lower on figural reasoning than younger executives, and much lower on a letter series test of inductive reasoning. Other measures of inductive reasoning, such as Raven's Advanced Progressive Matrices, also showed similar age group mean differences across settings. Implications for employee selection and adverse impact on older job candidates are discussed.

Introducing the special section on openness to experience: review of openness taxonomies, measurement, and nomological net.

In this introduction to the Special Section on Openness to Experience, we review the historical background of the construct and its measurement. We also provide a meta-analytically based review of its broader nomological net. Specifically, we review relationships with other individual differences constructs, including personality traits, interests, and cognitive ability. We highlight the various roles that openness and intellect play in educational performance, occupational attitudes and behaviors, job performance, career success, and psychological health and well-being. In doing so, we emphasize the unique contributions of the articles published in this special section (Albrecht, Dilchert, Deller, & Paulus; Connelly, Ones, Davies, & Birkland; DeYoung, Quilty, Peterson, & Gray; Roets, Cornelis, & Van Hiel; Woo, Chernyshenko, Longley, Zhang, Chiu, & Stark; Woo, Chernyshenko, Stark, & Conz). Finally, we note fruitful venues for future research involving Openness constructs.

Opening up openness: a theoretical sort following critical incidents methodology and a meta-analytic investigation of the trait family measures.

Existing taxonomies of Openness's facet structure have produced widely divergent results, and there is limited comprehensive empirical evidence about how Openness-related scales on existing personality inventories align within the 5-factor framework. In Study 1, we used a critical incidents sorting methodology to identify 11 categories of Openness measures; in Study 2, we meta-analyzed the relationships of these categories with global markers of the Big Five traits (utilizing data from 106 samples with a total sample size of N = 35,886). Our results identified 4 true facets of Openness: aestheticism, openness to sensations, nontraditionalism, and introspection. Measures of these facets were unadulterated by variance from other Big Five traits. Many traits frequently conceptualized as facets of Openness (e.g., innovation/creativity, variety-seeking, and tolerance) emerged as trait compounds that, although related to Openness, are also dependent on other Big Five traits. We discuss how Openness should be conceptualized, measured, and studied in light of the empirically based, refined taxonomy emerging from this research.

Mechanical versus clinical data combination in selection and admissions decisions: a meta-analysis.

In employee selection and academic admission decisions, holistic (clinical) data combination methods continue to be relied upon and preferred by practitioners in our field. This meta-analysis examined and compared the relative predictive power of mechanical methods versus holistic methods in predicting multiple work (advancement, supervisory ratings of performance, and training performance) and academic (grade point average) criteria. There was consistent and substantial loss of validity when data were combined holistically-even by experts who are knowledgeable about the jobs and organizations in question-across multiple criteria in work and academic settings. In predicting job performance, the difference between the validity of mechanical and holistic data combination methods translated into an improvement in prediction of more than 50%. Implications for evidence-based practice are discussed.

Integrity tests predict counterproductive work behaviors and job performance well: comment on Van Iddekinge, Roth, Raymark, and Odle-Dusseau (2012).

Examination of the Van Iddekinge, Roth, Raymark, and Odle-Dusseau (2012) meta-analysis reveals a number of problems. They meta-analyzed a partial database of integrity test validities. An examination of their coded database revealed that measures coded as integrity tests and meta-analyzed as such often included scales that are not in fact integrity tests. In addition, there were important deficiencies in their analytic approach relating to application of range restriction corrections and identification of moderators. We found the absence of fully hierarchical moderator analyses to be a serious weakness. We also explain why empirical comparisons between test publishers versus non-publishers cannot unambiguously lead to inferences of bias, as alternate explanations are possible, even likely. In light of the problems identified, it appears that the conclusions about integrity test validity drawn by Van Iddekinge et al. cannot be considered accurate or reliable.

Samples in applied psychology: over a decade of research in review.

This study examines sample characteristics of articles published in Journal of Applied Psychology (JAP) from 1995 to 2008. At the individual level, the overall median sample size over the period examined was approximately 173, which is generally adequate for detecting the average magnitude of effects of primary interest to researchers who publish in JAP. Samples using higher units of analyses (e.g., teams, departments/work units, and organizations) had lower median sample sizes (Mdn ≈ 65), yet were arguably robust given typical multilevel design choices of JAP authors despite the practical constraints of collecting data at higher units of analysis. A substantial proportion of studies used student samples (~40%); surprisingly, median sample sizes for student samples were smaller than working adult samples. Samples were more commonly occupationally homogeneous (~70%) than occupationally heterogeneous. U.S. and English-speaking participants made up the vast majority of samples, whereas Middle Eastern, African, and Latin American samples were largely unrepresented. On the basis of study results, recommendations are provided for authors, editors, and readers, which converge on 3 themes: (a) appropriateness and match between sample characteristics and research questions, (b) careful consideration of statistical power, and (c) the increased popularity of quantitative synthesis. Implications are discussed in terms of theory building, generalizability of research findings, and statistical power to detect effects.

Delineating the construct network of the Personnel Reaction Blank: associations with externalizing tendencies and normal personality.

Integrity testing has long been utilized in personnel selection to screen for tendencies toward counterproductive workplace behaviors. The construct of externalizing from the psychopathology literature represents a coherent spectrum marked by disinhibitory traits and behaviors. The present study drew on a sample of male and female undergraduates to examine the construct network of the Personnel Reaction Blank (PRB; H. G. Gough, R. D. Arvey, & P. Bradley, 2004), a measure of integrity, in relation to externalizing as well as normal-range personality constructs assessed by the Multidimensional Personality Questionnaire (MPQ; A. Tellegen & N. G. Waller, 2008). Results revealed moderate to strong associations between several PRB scales and externalizing, which were largely accounted for by MPQ traits subsumed by Negative Emotionality and Constraint. After accounting for MPQ traits in the prediction of externalizing, a modest predictive increment was achieved when adding the PRB scales, particularly biographical indicators from the Prosocial Background subscale. The findings highlight externalizing as a focal criterion for scale development in the integrity testing literature and help delineate the construct network of the PRB within the domains of personality and psychopathology.

An other perspective on personality: meta-analytic integration of observers' accuracy and predictive validity.

The bulk of personality research has been built from self-report measures of personality. However, collecting personality ratings from other-raters, such as family, friends, and even strangers, is a dramatically underutilized method that allows better explanation and prediction of personality's role in many domains of psychology. Drawing hypotheses from D. C. Funder's (1995) realistic accuracy model about trait and information moderators of accuracy, we offer 3 meta-analyses to help researchers and applied psychologists understand and interpret both consistencies and unique insights afforded by other-ratings of personality. These meta-analyses integrate findings based on 44,178 target individuals rated across 263 independent samples. Each meta-analysis assessed the accuracy of observer ratings, as indexed by interrater consensus/reliability (Study 1), self-other correlations (Study 2), and predictions of behavior (Study 3). The results show that although increased frequency of interacting with targets does improve accuracy in rating personality, informants' interpersonal intimacy with the target is necessary for substantial increases in other-rating accuracy. Interpersonal intimacy improved accuracy especially for traits low in visibility (e.g., Emotional Stability) but only minimally for traits high in evaluativeness (e.g., Agreeableness). In addition, observer ratings were strong predictors of behaviors. When the criterion was academic achievement or job performance, other-ratings yielded predictive validities substantially greater than and incremental to self-ratings. These findings indicate that extraordinary value can gained by using other-reports to measure personality, and these findings provide guidelines toward enriching personality theory. Various subfields of psychology in which personality variables are systematically assessed and utilized in research and practice can benefit tremendously from use of others' ratings to measure personality variables.