Getting to the core: How “(dis)honest” is the core of the Dark Triad?

Giving Meaning to the Dark Triad: Comparison of Different Factor Structures of the Dirty Dozen Through Eight Regions of the World

The traits of the dark triad (narcissism, psychopathy, and Machiavellianism) capture the individual differences in the aversive personality. The dark triad has shown significant relations with behaviors that affect people's lives. One of the best-known instruments to assess the dark triad is the Dirty Dozen. However, controversy continues over the use of one general dark triad score or, conversely, three different scores. This study aimed to investigate the factor structure of the Dirty Dozen across eight global regions. There were 11,477 participants in 49 countries grouped into eight regions. Different factor structures were studied using confirmatory factor analyses. Both the three-dimensional models and the bifactor models (symmetrical or traditional and non-symmetrical or bifactor-[S - 1]) showed a good fit to the data. The bifactor-(S - 1) models (with psychopathy or Machiavellianism as the reference factors) show adequate fit to the data, supported by the coherence of the factorial loadings and the bifactor indices. Regarding measurement invariance for both models, configural, metric, and scalar invariance were satisfied. The results indicate that it is not clear whether a psychopathy or Machiavellianism reference factor predominates in the Dirty Dozen. For both models, templates are provided to obtain standardized scores for applied researchers in the eight studied world regions until future studies offer a greater amount of validity evidence for this instrument.

Bifactor exploratory structural equation modeling: A meta-analytic review of model fit

Multivariate behavioral research often focuses on latent constructs—such as motivation, self-concept, or wellbeing—that cannot be directly observed. Typically, these latent constructs are measured with items in standardized instruments. To test the factorial structure and multidimensionality of latent constructs in educational and psychological research, Morin et al. (2016a) proposed bifactor exploratory structural equation modeling (B-ESEM). This meta-analytic review (158 studies, k = 308, N = 778,624) aimed to estimate the extent to which B-ESEM model fit differs from other model representations, including confirmatory factor analysis (CFA), exploratory structural equation modeling (ESEM), hierarchical CFA, hierarchical ESEM, and bifactor-CFA. The study domains included learning and instruction, motivation and emotion, self and identity, depression and wellbeing, and interpersonal relations. The meta-analyzed fit indices were the χ²/df ratio, the comparative fit index (CFI), the Tucker-Lewis index (TLI), the root mean square error of approximation (RMSEA), and the standardized root mean squared residual (SRMR). The findings of this meta-analytic review indicate that the B-ESEM model fit is superior to the fit of reference models. Furthermore, the results suggest that model fit is sensitive to sample size, item number, and the number of specific and general factors in a model.

Honesty as a trait

The purpose of this paper is to review recent research about the possibility that some people are more honest than others and about the causes of them being so. We tackle four big questions about the consistency of honest behavior, the content and breadth of trait honesty, the mechanisms underlying trait honesty, and the measurement of trait honesty. Recent research reveals we are only at the beginning states of answering these questions about honesty. Invigorated research is needed to firmly resolve whether individuals differ in honesty and if so, integrate the determining mechanisms and develop strong measurements.

Dark triads, tetrads, tents, and cores: Why navigate (research) the jungle of dark personality models without a compass (criterion)?

This comprehensive review summarizes and evaluates the present state of the Dark Triad research literature (or more broadly, the dark personality trait literature), and as such serves both a pedagogical purpose, by providing an introduction or primer on the dark personality literature and a scientific purpose by directing future research on key issues that still have not been sufficiently addressed. In this review, we discuss and critique current operational conceptualizations of what it means for a personality trait to be classified as 'dark'. Also discussed is the Dark Core, as well as quantitative issues such as limitations of commonly used statistical treatments, such as multivariate analyses, bifactor modeling, and composite measures, and proposed solutions to some of these issues. Based on a comprehensive and critical appraisal of the literature, future directions are suggested to drive the dark trait field towards a more organized, parsimonious, and productive future.