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We used exploratory structural equation modeling to examine gender-based measurement invariance (MI) in the HEXACO-100 across three samples that varied in terms of age (undergraduate students in Study 1, working adults in Studies 2 and 3) and testing context (research context in Studies 1 and 2, high-stakes selection context in Study 3). Across three studies, we consistently found support for configural and metric invariance but not scalar invariance. However, the effect size measures of non-invariance were generally small. That said, in the Emotionality scale, for the same latent score, females scored higher than males due to measurement non-invariance (between 0.26 and 0.48 standard deviation units). Thus, the observed mean gender differences overestimated the true mean gender differences. The current study provides detailed evidence regarding gender-based MI of HEXACO personality scales. More generally, it provides insight regarding the effect that measurement artifacts can have on understanding psychological gender differences at the latent level.

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We present psychometric evidence for the BFAS-40, an abbreviated measure of the Big Five Aspects Scale (DeYoung et al., 2007). In Study 1, we developed the BFAS-40 using metaheuristic algorithms and cross-validated the factor structure of the shortened measure. In Study 2, we demonstrated that the BFAS and BFAS-40 correlate with external criteria in similar ways. In Studies 3 and 4, we provide convergent validity evidence by examining correlations between the BFAS-40 and other measures of typical and clinically relevant personality. Finally, in Study 5, we provide evidence of test-retest reliability as well as additional construct validity evidence. Across these five studies, we demonstrate that the BFAS-40 is a short, reliable, and valid measure of the Big Five Aspects.

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Organizational scientists have historically assessed personality via self-reports, but there is a growing recognition that personality ratings from observers offer superior prediction of job performance compared to targets' self-reports. Yet, the origin of these differences remains unclear: do observers show predictive validity advantages (a) because they have a clearer lens into how targets' thoughts, feelings, and desires translate to their behaviors (traits), (b) because they infer personality from how targets characteristically adapt their behaviors to situations (reputation), or (c) because they omit targets' unexpressed, internal aspects of personality (identity)? With a sample of 422 cadets at a highly selective military educational institute in South Korea, we applied (McAbee & Connelly, 2016) Trait-Reputation-Identity (TRI) Model to decompose consensus and discrepancy in multirater personality data. The variance associated with reputations (the unique personality insights held by observers) dominated the prediction for conscientiousness and agreeableness in predicting all criteria. Trait factors (reflecting the consensus between self- and observer-reports) were moderately related to ratings of job performance, citizenship, and grades for most theoretically aligned personality dimensions. Identity factors (targets' unique personality self-views) were generally unrelated to performance criteria, save for some modest positive relationships for conscientiousness (predicting work and academic performance) and agreeableness (predicting citizenship). These findings suggest that personality is an important determinant of success less by depicting "who employees are" (or "who they think they are") but more by describing "what employees do." We discuss the implications of these results for how multirater assessments can be built into organizational psychology research and practice. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

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The essence of measurement invariance (MI) analysis is to test the assumption that observed scores on a scale accurately reflect respondents' standings on a measured construct. Based on exploratory structural equation modeling, the current study examines gender-based MI in two Big Five measures of personality: the Mini-IPIP, and the Big Five Inventory (BFI) facet scales. We report results for MI based on both model fit indices and a practical significance index that quantifies the extent of noninvariance (i.e., dMACS). From the latter, we partition the observed group mean differences in scale scores into construct-irrelevant group differences versus construct-relevant group differences. In measures of Agreeableness, Conscientiousness, Extraversion, and Neuroticism across instruments, results supported metric invariance but not scalar invariance. That said, findings of statistical noninvariance were generally small in terms of practical effects, although some notable variability in the effects was evident. Overall, the current results provide evidence regarding gender-based MI of Big Five personality measures that are more detailed than that provided in past work. More generally, this study also provides useful guidance for future researchers investigating both the statistical and practical significance of measurement invariance.

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Exploratory bifactor models with keying factors were applied to item response data for the NEO-FFI-3 and HEXACO-PI-R questionnaires. Loadings on a general factor and positive and negative keying factors correlated with independent estimates of item valence, suggesting that item valence influences responses to these questionnaires. Correlations between personality domain scores and measures of self-esteem, depression, and positive and negative affect were all reduced significantly when the influence of evaluative content represented by the general and keying factors was removed. Findings support the need to model personality inventories in ways that capture reactions to evaluative item content.

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Personality and social psychology have historically been divided between personality researchers who study the impact of traits and social-cognitive researchers who study errors in trait judgments. However, a broader view of personality incorporates not only individual differences in underlying traits but also individual differences in the distinct ways a person's personality is construed by oneself and by others. Such unique insights are likely to appear in the idiosyncratic personality judgments that raters make and are likely to have etiologies and causal force independent of trait perceptions shared across raters. Drawing on the logic of the Johari window (Luft & Ingham, 1955), the Self-Other Knowledge Asymmetry Model (Vazire, 2010), and Socioanalytic Theory (Hogan, 1996; Hogan & Blickle, 2013), we present a new model that separates personality variance into consensus about underlying traits (Trait), unique self-perceptions (Identity), and impressions conveyed to others that are distinct from self-perceptions (Reputation). We provide three demonstrations of how this Trait-Reputation-Identity (TRI) Model can be used to understand (a) consensus and discrepancies across rating sources, (b) personality's links with self-evaluation and self-presentation, and (c) gender differences in traits. We conclude by discussing how researchers can use the TRI Model to achieve a more sophisticated view of personality's impact on life outcomes, developmental trajectories, genetic origins, person-situation interactions, and stereotyped judgments. (PsycINFO Database Record

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The present study examines the consequences of perceived interpersonal discrimination on stress, health, and performance in a sample of 210 science, technology, engineering, and mathematics (STEM) academicians. Using a path model, we test the relation that perceived interpersonal discrimination has on stress and the relation of stress to physical health maladies and on current and future performance. In so doing, we assess the link between discrimination and decrements in performance over time. Additionally, we test supervisor social support as a moderator of the discrimination-stress relation. Findings support relations between perceived interpersonal discrimination and stress, which in turn relates to declines in physical health and performance outcomes. Moreover, supervisory support is shown to mitigate the influence of interpersonal discrimination on stress in STEM academicians.

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Working memory capacity is one of the most frequently measured individual difference constructs in cognitive psychology and related fields. However, implementation of complex span and other working memory measures is generally time-consuming for administrators and examinees alike. Because researchers often must manage the tension between limited testing time and measuring numerous constructs reliably, a short and effective measure of working memory capacity would often be a major practical benefit in future research efforts. The current study developed a shortened computerized domain-general measure of working memory capacity by representatively sampling items from three existing complex working memory span tasks: operation span, reading span, and symmetry span. Using a large archival data set (Study 1, N = 4,845), we developed and applied a principled strategy for developing the reduced measure, based on testing a series of confirmatory factor analysis models. Adequate fit indices from these models lent support to this strategy. The resulting shortened measure was then administered to a second independent sample (Study 2, N = 172), demonstrating that the new measure saves roughly 15 min (30%) of testing time on average, and even up to 25 min depending on the test-taker. On the basis of these initial promising findings, several directions for future research are discussed.

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Interest in the role of personality traits in predicting academic performance outcomes has steadily increased over the last several decades, enough to produce a number of meta-analyses that summarize this research (e.g., Poropat, 2009; Richardson, Abraham, & Bond, 2012). These previous meta-analyses combine a variety of alternative personality measures under the assumption that they all reflect the same personality traits and thus predict outcomes similarly. The current meta-analysis tests this assumption by comparing different personality measures when predicting postsecondary grade point average (GPA). The operational validities (r+) of 5 frequently used measures of the Big Five personality traits were compared: the NEO Personality Inventory--Revised (NEO-PI-R; Costa & McCrae, 1992), the NEO Five-Factor Inventory (NEO-FFI; Costa & McCrae, 1992), the Big Five Inventory (BFI; e.g., Benet-Martínez & John, 1998), Goldberg's (1992) unipolar Big Five Factor Markers (Markers), and the Big Five International Personality Item Pool (IPIP; Goldberg, 1999). A systematic review of the psychological literature from 1992 to 2012 was conducted, identifying 51 studies containing 274 correlations. Conscientiousness demonstrated the strongest criterion-related validity for predicting GPA (r+ = .23), consistent with previous meta-analyses; in addition, this overall validity was found to be robust across measures (r(BFI)(+) = .24, r(IPIP)(+) = .21, r(Markers)(+) = .15, r(NEO-FFI)(+) = .24, r(NEO-PI-R)(+) = .26). Although the criterion-related validities for Extraversion, Agreeableness, Neuroticism, and Openness to Experience (Intellect) differed by measure, they were generally low (r+s < .10). Practical implications of the findings and directions for future research are discussed.

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