Personality and leadership: Meta-analytic review of cross-cultural moderation, behavioral mediation, and honesty-humility.

We advance the trait approach to leadership by leveraging a large multinational database on leader emergence (k = 120 samples, N = 32,579) and leader effectiveness (k = 116, N = 42,487) to extend Judge et al.'s (2002) classic meta-analysis of Big Five personality and leadership. By testing novel hypotheses rooted in culturally endorsed implicit leadership theory and socioanalytic theory, we offer three unique insights. First, in collectivist societies (cultures that value interdependence with one's group), the five factor model traits-and leader Extraversion and Agreeableness in particular-are stronger predictors of leader effectiveness, consistent with the theorized need for enhanced social coordination in such cultures. Second, a theoretical model is proposed to specify that leader Big Five trait effects are mediated by leader behavior (confirming that Consideration mediates Extraversion and Agreeableness, whereas Initiating Structure mediates Conscientiousness, Extraversion, and Openness). Third, trait Honesty-Humility robustly predicts leader effectiveness beyond the Big Five traits, expanding the trait approach. New implications for understanding when and why personality traits predict leadership are discussed. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Adverse impact reduction and job performance optimization via pareto-optimal weighting: A shrinkage formula and regularization technique using machine learning.

In personnel selection practice, one useful technique for reducing adverse impact and enhancing diversity is the Pareto-optimal weighting approach of De Corte et al. (2007). This approach produces a series of hiring solutions that characterize a diversity-job performance trade-off and can lead to more optimal selection outcomes (sometimes doubling the number of job offers for minority applicants without changing the job performance outcomes of personnel selection). Despite these advantages, recent research has identified a potential problem with the Pareto-weighting technique-Pareto solutions suffer from shrinkage upon cross-validation. To address the problem of shrinkage in the Pareto trade-off curve (i.e., diversity shrinkage and validity shrinkage), we offer two contributions. First, a shrinkage approximation formula is introduced (similar to a formula for adjusted R², but applicable to the entire Pareto trade-off curve). Second, we derive a novel technique for the regularization of Pareto-optimal predictor weights (borrowed from the field of machine learning), which is designed to produce predictor weights that are less vulnerable to shrinkage (similar to ridge regression and adapted from the elastic net technique). Both approaches-the proposed Pareto shrinkage formula and the proposed regularization technique-are then evaluated using Monte Carlo simulation. Recommendations are provided for approximating potential diversity-performance trade-off curves in personnel selection, while accounting for shrinkage. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Emotional Intelligence and Transformational Leadership: Meta-Analysis and Explanatory Model of Female Leadership Advantage.

Emotional intelligence is a second-stratum factor of general intelligence (MacCann et al. 2014) that: (a) has been popularly touted as an essential individual difference for effective leadership (Goleman 1998), but also (b) exhibits large gender group differences favoring women (Joseph and Newman 2010). Combining these insights, we propose that emotional intelligence is a key mechanism in the so-called female leadership advantage (Eagly and Carli 2003-which emphasizes the finding that women are rated slightly higher in transformational leadership compared to men). The current study seeks to explain this gender leadership gap by specifying three personality-based theoretical mechanisms that enhance transformational leadership: (a) emotional intelligence (favoring women), (b) communion (stereotypical femininity; favoring women; Hsu et al. 2021), as well as an offsetting effect of (c) agency (stereotypical masculinity; favoring men). Meta-analytic data (including original meta-analyses among the leader's ability-based emotional intelligence, transformational leadership, communion, and agency) are used to test our theorized model. Results confirm the full mediation model of female leadership advantage. Because the three unique mechanisms operate in different directions, their individual indirect effects are notable, but their cumulative indirect effect is small and near-zero. In conclusion, we emphasize incorporating emotional intelligence with other personality-based explanations of gender effects in leadership perceptions.

Vocational interests and adverse impact: How attraction and selection on vocational interests relate to adverse impact potential.

The current research proposes to incorporate vocational interests into the study of adverse impact (i.e., differential hiring/selection rates between minority and majority groups in employment settings). In the context of high stakes testing (e.g., using cognitive and personality tests), we show how race gaps in vocational interests would correspond to differential rates of job attraction (the attraction process) and various personnel selection outcomes (the selection process), in patterns that are not always intuitive. Using findings from various meta-analyses, we construct a combined correlation matrix of race, vocational interests, cognitive ability, and Conscientiousness; and provide mathematical formulas to assess the role of vocational interests in determining subgroup differences on predictors in applicant pools. Results and empirical examples suggest: (a) applicant attraction based on vocational interests can reduce adverse impact potential when the interest favors the minority [majority] group and is negatively [positively] related to the predictor; (b) attraction effects of vocational interests on adverse impact potential are modest; (c) if the vocational interest subgroup mean difference is small relative to other predictors in use, personnel selection on the interest will reduce adverse impact potential; (d) attraction effects tend to dampen or remove the selection effects of vocational interests on adverse impact potential, due to variance restriction on interests in the applicant pool; and (e) selection effects tend to be much stronger than attraction effects. These findings have implications for how adverse impact might differ systematically across job types, partly due to attraction and selection effects involving race differences in vocational interests. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Teammate Invitation Networks: The Roles of Recommender Systems and Prior Collaboration in Team Assembly.

Teammate invitation networks are foundational for team assembly, and recommender systems (similar to dating websites, but for selecting potential teammates) can aid the formation of such networks. This paper extends Hinds, Carley, Krackhardt, and Wholey's (2000) influential model of team member selection by incorporating online recommender systems. Exponential random graph modeling of two samples (overall N = 410; 63 teams; 1,048 invitations) shows the invitation network is predicted by online recommendations, beyond previously-established effects of prior collaboration/familiarity, skills/competence, and homophily. Importantly, online recommendations are less heeded when there is prior collaboration (effect replicates across samples). This study highlights technology-enabled team assembly from a network perspective.

Diversity shrinkage: Cross-validating pareto-optimal weights to enhance diversity via hiring practices.

To reduce adverse impact potential and improve diversity outcomes from personnel selection, one promising technique is De Corte, Lievens, and Sackett's (2007) Pareto-optimal weighting strategy. De Corte et al.'s strategy has been demonstrated on (a) a composite of cognitive and noncognitive (e.g., personality) tests (De Corte, Lievens, & Sackett, 2008) and (b) a composite of specific cognitive ability subtests (Wee, Newman, & Joseph, 2014). Both studies illustrated how Pareto-weighting (in contrast to unit weighting) could lead to substantial improvement in diversity outcomes (i.e., diversity improvement), sometimes more than doubling the number of job offers for minority applicants. The current work addresses a key limitation of the technique-the possibility of shrinkage, especially diversity shrinkage, in the Pareto-optimal solutions. Using Monte Carlo simulations, sample size and predictor combinations were varied and cross-validated Pareto-optimal solutions were obtained. Although diversity shrinkage was sizable for a composite of cognitive and noncognitive predictors when sample size was at or below 500, diversity shrinkage was typically negligible for a composite of specific cognitive subtest predictors when sample size was at least 100. Diversity shrinkage was larger when the Pareto-optimal solution suggested substantial diversity improvement. When sample size was at least 100, cross-validated Pareto-optimal weights typically outperformed unit weights-suggesting that diversity improvement is often possible, despite diversity shrinkage. Implications for Pareto-optimal weighting, adverse impact, sample size of validation studies, and optimizing the diversity-job performance tradeoff are discussed. (PsycINFO Database Record

Explaining the black-white gap in cognitive test scores: Toward a theory of adverse impact.

In understanding the causes of adverse impact, a key parameter is the Black-White difference in cognitive test scores. To advance theory on why Black-White cognitive ability/knowledge test score gaps exist, and on how these gaps develop over time, the current article proposes an inductive explanatory model derived from past empirical findings. According to this theoretical model, Black-White group mean differences in cognitive test scores arise from the following racially disparate conditions: family income, maternal education, maternal verbal ability/knowledge, learning materials in the home, parenting factors (maternal sensitivity, maternal warmth and acceptance, and safe physical environment), child birth order, and child birth weight. Results from a 5-wave longitudinal growth model estimated on children in the NICHD Study of Early Child Care and Youth Development from ages 4 through 15 years show significant Black-White cognitive test score gaps throughout early development that did not grow significantly over time (i.e., significant intercept differences, but not slope differences). Importantly, the racially disparate conditions listed above can account for the relation between race and cognitive test scores. We propose a parsimonious 3-Step Model that explains how cognitive test score gaps arise, in which race relates to maternal disadvantage, which in turn relates to parenting factors, which in turn relate to cognitive test scores. This model and results offer to fill a need for theory on the etiology of the Black-White ethnic group gap in cognitive test scores, and attempt to address a missing link in the theory of adverse impact.

Why does self-reported emotional intelligence predict job performance? A meta-analytic investigation of mixed EI.

Recent empirical reviews have claimed a surprisingly strong relationship between job performance and self-reported emotional intelligence (also commonly called trait EI or mixed EI), suggesting self-reported/mixed EI is one of the best known predictors of job performance (e.g., ρ = .47; Joseph & Newman, 2010b). Results further suggest mixed EI can robustly predict job performance beyond cognitive ability and Big Five personality traits (Joseph & Newman, 2010b; O'Boyle, Humphrey, Pollack, Hawver, & Story, 2011). These criterion-related validity results are problematic, given the paucity of evidence and the questionable construct validity of mixed EI measures themselves. In the current research, we update and reevaluate existing evidence for mixed EI, in light of prior work regarding the content of mixed EI measures. Results of the current meta-analysis demonstrate that (a) the content of mixed EI measures strongly overlaps with a set of well-known psychological constructs (i.e., ability EI, self-efficacy, and self-rated performance, in addition to Conscientiousness, Emotional Stability, Extraversion, and general mental ability; multiple R = .79), (b) an updated estimate of the meta-analytic correlation between mixed EI and supervisor-rated job performance is ρ = .29, and (c) the mixed EI-job performance relationship becomes nil (ß = -.02) after controlling for the set of covariates listed above. Findings help to establish the construct validity of mixed EI measures and further support an intuitive theoretical explanation for the uncommonly high association between mixed EI and job performance--mixed EI instruments assess a combination of ability EI and self-perceptions, in addition to personality and cognitive ability.

Differential susceptibility to effects of maternal sensitivity? A study of candidate plasticity genes.

Here we tested whether there was genetic moderation of effects of early maternal sensitivity on social-emotional and cognitive-linguistic development from early childhood onward and whether any detected Gene × Environment interaction effects proved consistent with differential-susceptibility or diathesis-stress models of Person × Environment interaction (N = 695). Two new approaches for evaluating models were employed with 12 candidate genes. Whereas maternal sensitivity proved to be a consistent predictor of child functioning across the primary-school years, candidate genes did not show many main effects, nor did they tend to interact with maternal sensitivity/insensitivity. These findings suggest that the developmental benefits of early sensitive mothering and the costs of insensitive mothering look more similar than different across genetically different children in the current sample. Although acknowledgement of this result is important, it is equally important that the generally null Gene × Environment results reported here not be overgeneralized to other samples, other predictors, other outcomes, and other candidate genes.

Gender differences in narcissism: a meta-analytic review.

Despite the widely held belief that men are more narcissistic than women, there has been no systematic review to establish the magnitude, variability across measures and settings, and stability over time of this gender difference. Drawing on the biosocial approach to social role theory, a meta-analysis performed for Study 1 found that men tended to be more narcissistic than women (d = .26; k = 355 studies; N = 470,846). This gender difference remained stable in U.S. college student cohorts over time (from 1990 to 2013) and across different age groups. Study 1 also investigated gender differences in three facets of the Narcissistic Personality Inventory (NPI) to reveal that the narcissism gender difference is driven by the Exploitative/Entitlement facet (d = .29; k = 44 studies; N = 44,108) and Leadership/Authority facet (d = .20; k = 40 studies; N = 44,739); whereas the gender difference in Grandiose/Exhibitionism (d = .04; k = 39 studies; N = 42,460) was much smaller. We further investigated a less-studied form of narcissism called vulnerable narcissism-which is marked by low self-esteem, neuroticism, and introversion-to find that (in contrast to the more commonly studied form of narcissism found in the DSM and the NPI) men and women did not differ on vulnerable narcissism (d = -.04; k = 42 studies; N = 46,735). Study 2 used item response theory to rule out the possibility that measurement bias accounts for observed gender differences in the three facets of the NPI (N = 19,001). Results revealed that observed gender differences were not explained by measurement bias and thus can be interpreted as true sex differences. Discussion focuses on the implications for the biosocial construction model of gender differences, for the etiology of narcissism, for clinical applications, and for the role of narcissism in helping to explain gender differences in leadership and aggressive behavior. Readers are warned against overapplying small effect sizes to perpetuate gender stereotypes.

Emotional intelligence is a second-stratum factor of intelligence: evidence from hierarchical and bifactor models.

This article examines the status of emotional intelligence (EI) within the structure of human cognitive abilities. To evaluate whether EI is a 2nd-stratum factor of intelligence, data were fit to a series of structural models involving 3 indicators each for fluid intelligence, crystallized intelligence, quantitative reasoning, visual processing, and broad retrieval ability, as well as 2 indicators each for emotion perception, emotion understanding, and emotion management. Unidimensional, multidimensional, hierarchical, and bifactor solutions were estimated in a sample of 688 college and community college students. Results suggest adequate fit for 2 models: (a) an oblique 8-factor model (with 5 traditional cognitive ability factors and 3 EI factors) and (b) a hierarchical solution (with cognitive g at the highest level and EI representing a 2nd-stratum factor that loads onto g at λ = .80). The acceptable relative fit of the hierarchical model confirms the notion that EI is a group factor of cognitive ability, marking the expression of intelligence in the emotion domain. The discussion proposes a possible expansion of Cattell-Horn-Carroll theory to include EI as a 2nd-stratum factor of similar standing to factors such as fluid intelligence and visual processing.

More than g: selection quality and adverse impact implications of considering second-stratum cognitive abilities.

When using cognitive tests, personnel selection practitioners typically face a trade-off between the expected job performance and diversity of new hires. We review the increasingly mainstream evidence that cognitive ability is a multidimensional and hierarchically ordered set of concepts, and examine the implications for both composite test validity and subgroup differences. Ultimately, we recommend a strategy for differentially weighting cognitive subtests (i.e., second-stratum abilities) in a way that minimizes overall subgroup differences without compromising composite test validity. Using data from 2 large validation studies that included a total of 15 job families, we demonstrate that this strategy could lead to substantial improvement in diversity hiring (e.g., doubling the number of job offers extended to minority applicants) and to at least 8% improvement in job offers made to minority applicants, without decrements in expected selection quality compared to a unit-weighted cognitive test composite. Finally, we conduct a sensitivity analysis to examine whether the technique continues to perform well when applied to applicant pools of smaller size. We discuss prerequisites for the application of this strategy, potential limitations, and extensions.

Distinguishing differential susceptibility from diathesis-stress: recommendations for evaluating interaction effects.

This report describes the state of the art in distinguishing data generated by differential susceptibility from diathesis-stress models. We discuss several limitations of existing practices for probing interaction effects and offer solutions that are designed to better differentiate differential susceptibility from diathesis-stress models and quantify their corresponding implications. In addition, we demonstrate the utility of these methods by revisiting published evidence suggesting that temperamental difficulty serves as a marker of enhanced susceptibility to early maternal caregiving across a range of outcome domains in the NICHD Study of Early Child Care and Youth Development. We find that, with the exception of mother reports of psychopathology, there is consistent evidence in the Study of Early Child Care and Youth Development that the predictive significance of early sensitivity is moderated by difficult temperament over time. However, differential susceptibility effects emerged primarily for teacher reports of academic skills, social competence, and symptomatology. In contrast, effects more consistent with the diathesis-stress model were obtained for mother reports of social skills and objective tests of academic skills. We conclude by discussing the value of the application of this work to the next wave of Gene × Environment studies focused on early caregiving experiences.

Using the bioecological model to predict risk perception of marijuana use and reported marijuana use in adolescence.

PURPOSE: The purpose of the study was to investigate the ability of the Bioecological Model (BEM) to predict adolescents' risk perception (RP) of marijuana use and reported marijuana use. The secondary aim of the study was to investigate the extent to which the BEM influenced adolescents' decision-making regarding marijuana use by exploring the BEM's ability to moderate the relationship between adolescents' RP of marijuana use and reported use. METHODS: Systems in the proposed BEM included variables from the literature proven to influence adolescents' health risk behaviors. Hierarchical linear regression was used to predict RP from BEM variables. Hierarchical logistic regressions were used to predict marijuana use from BEM variables and to assess the ability of the BEM to moderate the relationship between RP and reported marijuana use. RESULTS: Three systems in the BEM, Adolescent, Microsystem, and Mesosystem, were predictive of RP and reported marijuana use. At least two variables in each system predicted RP and reported marijuana use. The Mesosystem moderated the relationship between RP and use. CONCLUSION: The combination of the BEM and the HBM provides the unique opportunity to understand adolescents' decision to engage in marijuana use. Because the BEM is viewed as part of a generative process, results here can be used to produce a more integrated HBM specific to adolescence.

Emotional intelligence: an integrative meta-analysis and cascading model.

Research and valid practice in emotional intelligence (EI) have been impeded by lack of theoretical clarity regarding (a) the relative roles of emotion perception, emotion understanding, and emotion regulation facets in explaining job performance; (b) conceptual redundancy of EI with cognitive intelligence and Big Five personality; and (c) application of the EI label to 2 distinct sets of constructs (i.e., ability-based EI and mixed-based EI). In the current article, the authors propose and then test a theoretical model that integrates these factors. They specify a progressive (cascading) pattern among ability-based EI facets, in which emotion perception must causally precede emotion understanding, which in turn precedes conscious emotion regulation and job performance. The sequential elements in this progressive model are believed to selectively reflect Conscientiousness, cognitive ability, and Neuroticism, respectively. "Mixed-based" measures of EI are expected to explain variance in job performance beyond cognitive ability and personality. The cascading model of EI is empirically confirmed via meta-analytic data, although relationships between ability-based EI and job performance are shown to be inconsistent (i.e., EI positively predicts performance for high emotional labor jobs and negatively predicts performance for low emotional labor jobs). Gender and race differences in EI are also meta-analyzed. Implications for linking the EI fad in personnel selection to established psychological theory are discussed.

The stability of personality traits in individuals with borderline personality disorder.

Although stability and pervasive inflexibility are general criteria for Diagnostic and Statistical Manual of Mental Disorders, 4th edition (American Psychiatric Association, 1994) personality disorders (PDs), borderline PD (BPD) is characterized by instability in several domains, including interpersonal behavior, affect, and identity. The authors hypothesized that such inconsistencies notable in BPD may relate to instability at the level of the basic personality traits that are associated with this disorder. Five types of personality trait stability across 4 assessments over 6 years were compared for BPD patients (N = 130 at first interval) and patients with other PDs (N = 302). Structural stability did not differ across groups. Differential stability tended to be lower for 5-factor model (FFM) traits in the BPD group, with the strongest and most consistent effects observed for Neuroticism and Conscientiousness. Growth curve models suggested that these 2 traits also showed greater mean-level change, with Neuroticism declining faster and Conscientiousness increasing faster, in the BPD group. The BPD group was further characterized by greater individual-level instability for Neuroticism and Conscientiousness in these models. Finally, the BPD group was less stable in terms of the ipsative configuration of FFM facet-level profiles than was the other PD group over time. Results point to the importance of personality trait instability in characterizing BPD.

Factorial invariance of child self-report across race/ethnicity groups: a multigroup confirmatory factor analysis approach utilizing the PedsQL 4.0 Generic Core Scales.

PURPOSE: In order to compare health-related quality of life (HRQOL) research findings across race/ethnicity subpopulations, it is important to demonstrate factorial invariance, i.e., that the items have equivalent meaning across the race/ethnicity groups studied. This study examined the factorial invariance of child self-reported HRQOL across race/ethnicity groups for ages 5-18 years utilizing the 23-item PedsQL 4.0 Generic Core Scales. METHODS: Multigroup confirmatory factor analysis (CFA) was performed, specifying a five-factor model across four race/ethnicity groups (White Non-Hispanic, Hispanic, Asian/Pacific Islander, Black Non-Hispanic). Multigroup structural equation models were proposed in order to compare the factor structure across the four race/ethnicity subpopulations. The analyses were based on 5,490 children recruited from clinic, school, and community populations. RESULTS: Strict factorial invariance across the four race/ethnicity groups was demonstrated based on stability of the Comparative Fit Index (CFI) between the models, and several additional indices of practical fit including the Root Mean Squared Error of Approximation (RMSEA), the Non-Normed Fit Index (NNFI), and the Parsimony Normed Fit Index (PNFI). CONCLUSIONS: The findings support an equivalent five-factor structure across the four race/ethnicity subpopulations studied. Based on these data, it can be concluded that children across the four race/ethnicity groups studied interpreted items in a similar manner regardless of their race/ethnicity.

Using factor analysis to confirm the validity of children's self-reported health-related quality of life across different modes of administration.

BACKGROUND: The measurement of pediatric health-related quality of life (HRQOL) in pediatric medicine and health services research has grown significantly over the past decade. While HRQOL instruments are often administered in clinic settings, alternative modes of administration are also utilized such as mail and telephone surveys. In order for comparisons across in-person, mail, and telephone administration to be valid, items on a HRQOL measure must have equivalent meaning across mode of administration. That is, they must demonstrate factorial invariance (stable factor structure) across mode of administration. PURPOSE: The objective of the present study was to implement the multigroup confirmatory factor analysis (CFA) method for invariance testing across mode of administration for children's self-reported HRQOL. METHODS: Multigroup CFA was performed specifying a five-factor model across three modes of administration groups (in-person, mail, and telephone survey). The 23-item PedsQL(TM) 4.0 Generic Core Scales was utilized as the measure of children's self-reported HRQOL in a sample of 3741 children ages 5-18. RESULTS: Strong factorial invariance across the mode of administration groups was demonstrated based on stability of the Comparative Fit Index (CFI) between the models, and several additional indices of practical fit including the Root Mean Squared Error of Approximation (RMSEA), the Non-Normed Fit Index (NNFI), and the Parsimony Normed Fit Index (PNFI). LIMITATIONS: The mode of administration subpopulations in our study differed with regard to health status. CONCLUSION: The multigroup CFA statistical methods utilized in the present study have important implications for clinical trials in which mixed modes of administration are used. The present findings support an equivalent five-factor structure of the PedsQL( TM) 4.0 Generic Core Scales across the three modes of administration studied. Based on these data, it can be concluded that children across the three modes of administration groups interpreted items on the PedsQL( TM) 4.0 Generic Core Scales in a similar manner.

Recruitment efforts to reduce adverse impact: targeted recruiting for personality, cognitive ability, and diversity.

Noting the presumed tradeoff between diversity and performance goals in contemporary selection practice, the authors elaborate on recruiting-based methods for avoiding adverse impact while maintaining aggregate individual productivity. To extend earlier work on the primacy of applicant pool characteristics for resolving adverse impact, they illustrate the advantages of simultaneous cognitive ability- and personality-based recruiting. Results of an algebraic recruiting model support general recruiting for cognitive ability, combined with recruiting for conscientiousness within the underrepresented group. For realistic recruiting effect sizes, this type of recruiting strategy greatly increases average performance of hires and percentage of hires from the underrepresented group. Further results from a policy-capturing study provide initial guidance on how features of organizational image can attract applicants with particular job-related personalities and abilities, in addition to attracting applicants on the basis of demographic background.