Relative and longitudinal evidence for the importance of the General Factor of Psychosocial Development in predicting well-being

The relationship between the General Factor of Psychosocial Development (GFPD) and well-being was examined. Support for three hypotheses was found. First, the GFPD accounted for more variance in well-being than the shared unique variance of the individual psychosocial stages. In fact, a number of the stages were negatively associated with well-being when controlling for the GFPD. Second, the GFPD accounted for a significant amount of variance in well-being when controlling for the General Factor of Personality. Third, the GFPD partially mediated the relationship between well-being at two points in time.     

Life history strategy, identity consolidation, and psychological well-being

Previous research has shown that individual differences in life history strategies co-vary with a large array of variables to the extent that latent variables from a number of psychological measures load on a single (Super-K) factor. Similar to research on the Super-K factor, the purpose of this study was to test the hypothesis that various measures of identity would load on a single factor and that this latent variable would in turn be associated with other variables reflecting life history strategy and psychological well-being, making a Super-K factor. A sample of 248 university students were administered a variety of questionnaires related to identity, life history strategy, and psychological well-being. Confirmatory factor analyses revealed the hypothesized Super-K factor and the relationship remained even when controlling for variance in social-desirable responding. The results are discussed in terms of the association between Erikson’s theory of psychosocial development and life history theory.     

A Review of Measures of Erikson’s Stages of Psychosocial Development: Evidence for a General Factor

Recent research suggests that values on Erikson’s psychosocial stages covary to form a general factor of psychosocial development (GFPD). The purpose of the current investigation was to further test this possibility by conducting a meta-analysis on the association among the psychosocial stages. Sixty-two correlation matrices from 50 different samples (N = 20,326) were analyzed. Factor analyses supported the existence of a GFPD. Future research should explore the nature of the GFPD.     

The General Factor of Personality and peer-rated social status: A rejoinder to de Vries (2011)

In a previous study we showed that self-reported Big Five scores and the General Factor of Personality (GFP) were related to peer-ratings of likeability and popularity (van der Linden, Scholte, et al., 2010). de Vries (2011a) re-analyzed our data and concluded that (i) there was no evidence of a GFP, and (ii) the GFP we used was latent factor of Extraversion. In this rejoinder I present arguments that compromise the re-analysis and conclusions as described by de Vries (2011a) and emphasize the relevance of the GFP.     

Misconstruing methods and meaning in the General Factor of Personality

Research has suggested that a General Factor of Personality (GFP) might represent a real and meaningful higher‐order factor in the personality hierarchy. However, there are psychometric shortcomings in many of the studies used to support this argument, as well as convincing empirical evidence for alternative explanations of the GFP as methodological rather than meaningful. The current article re‐examines the research supporting a substantive GFP by considering and evaluating the evidence presented in a recent volume (Just, 2011). It is concluded that covariation among first‐order personality factors is more likely a statistical or methodological artefact than a theoretically meaningful higher‐order construct.     

Evaluating the Evidence for the General Factor of Personality across Multiple Inventories

A general factor of personality (GFP) has been proposed as the apex of a personality trait hierarchy that explains covariance among the lower-order factors measured by various personality inventories. In this study we evaluated the GFP hypothesis across several personality inventories, unlike most previous research in which the GFP has been derived from individual instruments in isolation. Exploratory analyses did not produce substantial evidence for the existence of a single cross-instrument higher-order factor of factors and efforts to specify a range of GFP-inspired models in a confirmatory framework led to significant estimation difficulties and poor fit to the data. Overall these results fail to support a common GFP that is positioned at the top of a personality trait hierarchy.     

Evidence for bivariate systems: An empirical test of appetition and aversion across domains

Research in diverse domains of psychology has independently identified two behavioral systems, one concerned with obtaining positive outcomes, the other concerned with avoiding negative outcomes. This basic distinction, described in different domains of inquiry with varying terminology, may be integrated within a single appetitive–aversive systems model. The present research was designed to examine the viability of the appetitive–aversive distinction as an organizational construct underlying various particular measures and concepts. In four studies, individual difference measures from different domains were examined with exploratory (Study 1) and confirmatory (Studies 2–4) factor analyses. We expected and found that measures tapping sensitivity to rewards or positive outcomes would load on a common appetitive latent factor, whereas, measures tapping individual differences in sensitivity to punishment or negative outcomes would load a common aversive latent factor. Results strongly supported the hypothesized two-factor structure over alternative models and indicated that the latent appetitive and aversive variables accounted for about half the variance in the observed variables.     

The General Factor of Personality in selection and assessment samples

In two large samples (N₁ = 44,971, N₂ = 7793) we tested the General Factor of Personality (GFP) in the Big Five, measured during selection and assessment. A GFP could clearly be identified in the data, explaining approximately 50% of the Big Five variance. We found indications for socially desirable response tendencies in a subgroup that was tested for selection purposes. Yet, this tendency did not affect the personality factor structure or the GFP characteristics. Moreover, in the selection sample, the GFP was moderately related to the Overall Assessment Rating. The findings confirm the GFP in an applied setting and support the idea that the GFP does not merely reflect methodological artifacts but is substantive.     

The General Factor of Personality: A critical test

The present study provides evidence supporting the presence of a General Factor of Personality (GFP), which has been proposed to represent the apex of the hierarchy of personality traits. Furthermore, the construct validity of this general factor is assessed to address recent criticisms suggesting that the GFP may merely be a statistical artefact rather than a genuine higher-order personality dimension. In this study, two samples of monozygotic (MZ) and same-sex dizygotic (DZ) twins completed the NEO Personality Inventory-Revised (NEO-PI-IR), assessing individual differences in the Big Five traits of personality, and the Dimensional Assessment of Personality Problems-Differential Questionnaire (DAPP-DQ) measuring variance in abnormal personality traits. First unrotated factors were extracted from each of the two measures separately within each sample. Correlations between these factors were significant and high in both samples (.78 and .77), indicating that the factors represent similar constructs. The manner in which these findings help to validate the GFP is discussed.     

The General Factor of Personality: A reply to Muncer

In previous studies we have shown that a General Factor of Personality (GFP) occupies the apex of the hierarchy of personality as well as the apex of the personality disorders in the same way that g, the general factor of mental ability, occupies the apex in the organization of cognitive abilities (Rushton & Irwing, 2011). In a critique, Muncer (2011) re-analyzed one of our data sets and concluded there was no evidence for a GFP. He also argued against the evolutionary theory we had proposed for the origin of the GFP. In this rejoinder I rebut Muncer’s conclusion and describe how directional selection can explain the GFP.     

Factor analysis of the Beck Scale for Suicide Ideation with female suicide attempters

A sample of 119 female suicide attempters completed the Beck Scale for Suicide Ideation (BSS). Although confirmatory common factor analyses of BSS items failed to support previously hypothesized one-, two-, or three-factor models, confirmatory principal components analyses substantiated hypothesized one- and two-dimensional models. Heuristics for the number of factors converged on two latent dimensions and exploratory principal components analyses verified the presence of two previously hypothesized suicide ideation factors: motivation and preparation. Scales based on this two-dimensional model demonstrated convergent validity with other suicide indices.     

No evidence for a General Factor of Personality in the HEXACO Personality Inventory

There have been an increasing number of articles that have speculated on the existence of a General Factor of Personality (GFP) similar to ‘g’ in intelligence research. In this study, I provide evidence that this general factor may be an artifact of the personality instrument used. Specifically, in two samples I show that depending on the type of analysis used there is either no evidence for a GFP in the HEXACO Personality Inventory or the GFP is found to be uncorrelated to GFPs based on Big Five or FFM instruments.     

Evidence for the role of the General Factor of Personality (GFP) in enculturation: The GFP and self-construal in Japanese and American samples

Data from Midlife in the United States (MIDUS) studies, one with American participants and one with Japanese participants, were used to test the hypothesis that the General Factor of Personality (GFP) is positively associated with enculturation. To this end, the relationships between the GFP and independent self-construal and interdependent self-construal were examined. Consistent with the hypothesis, the results showed that an independent self-construal was more closely associated with the GFP in the American sample.     

Changing the general factor of personality and the c-fos gene expression with methylphenidate and self-regulation therapy

A deepening in the biological nature of the general factor of personality (GFP) is suggested: the activation level of the stress system is here represented by the gene expression of c-fos. The results of a single case experimental design are reported. A model of four coupled differential equations that explains the human personality dynamics as a consequence of a single stimulant drug intake has been fitted to psychological and biological experimental data. The stimulant-drug conditioning and its adaptation to the considered mathematical model is also studied for both kinds of measures. The dynamics of the c-fos expression presents a similar pattern to the dynamics of the psychological measures of personality assessed by the GFP-FAS (Five-Adjective Scale of the General Factor of Personality) as a consequence of a single dose of stimulant drug (methylphenidate). The model predicts similar dynamic patterns for both psychological and biological measures. This study proves that describing mathematically the dynamics of the effects of a stimulant drug as well as the effects of a conditioning method on psychological or subjective variables and on gene expression is possible. It verifies the existence of biological mechanisms underlying the dynamics of the General Factor of Personality (GFP).     

CFA Models with a General Factor and Multiple Sets of Secondary Factors

We propose a class of confirmatory factor analysis models that include multiple sets of secondary or specific factors and a general factor. The general factor accounts for the common variance among manifest variables, whereas multiple sets of secondary factors account for the remaining source-specific dependency among subsets of manifest variables. A special case of the model is further proposed which constrains the specific factor loadings to be proportional to the general factor loadings. This proportional model substantially reduces the number of model parameters while preserving the essential structure of the general model. Furthermore, the proportional model allows for the interpretation of latent variables as the expected values of the observed manifest variables, decomposition of the variances, and the inclusion of interactions, similar to generalizability theory. We provide two applications to illustrate the utility of the proposed class of models.     

A General Factor of Personality (GFP) from two meta-analyses of the Big Five: and

In two studies, we used structural equation models to test the hypothesis that a General Factor of Personality (GFP) occupies the apex of the hierarchy of personality. In Study 1, we found a GFP that explained 45% of the reliable variance in a model that went from the Big Five to the Big Two to the Big One in the 14 studies of inter-scale correlations (N = 4496) assembled by Digman (1997). A higher order factor of Alpha/Stability was defined by Conscientiousness, Emotional Stability, and Agreeableness, with loadings of from 0.61 to 0.70, while Beta/Plasticity was defined by Openness and Extraversion with loadings of 0.55 and 0.77. In turn, the GFP was defined by Alpha and Beta with loadings of 0.67. In Study 2, a GFP explained 44% of the reliable variance in a similar model using data from a published meta-analysis of the Big Five (N = 4000) by Mount, Barrick, Scullen, and Rounds (2005). Strong general factors such as these, based on large data sets with good model fits that cross validate perfectly, are unlikely to be due to artifacts and response sets.     

The general factor of personality and job performance: Revisiting previous meta‐analyses

The relationship between the General Factor of Personality (GFP) and several work‐related outcomes such as job performance and organizational citizenship behavior was examined using meta‐analytic data. Confirmatory factor analyses showed sizeable relationships between the GFP and various performance indicators ( = .34), larger than for any of the Big Five dimensions. Controlling for social desirability did not change the relationship between the GFP and job performance. Moreover, regression analyses showed that the GFP accounted for a larger part of the explained variance in the outcome measures than the unique variances of the Big Five. The results add to the evidence for the GFP as a social effectiveness factor and highlight the validity of the GFP in organizational contexts.     

Personality Correlates of Midlife Cardiometabolic Risk: The Explanatory Role of Higher‐Order Factors of the Five‐Factor Model

Varying associations are reported between Five‐Factor Model (FFM) personality traits and cardiovascular disease risk. Here, we further examine dispositional correlates of cardiometabolic risk within a hierarchical model of personality that proposes higher‐order traits of Stability (shared variance of Agreeableness, Conscientiousness, inverse Neuroticism) and Plasticity (Extraversion, Openness), and we test hypothesized mediation via biological and behavioral factors. In an observational study of 856 community volunteers aged 30–54 years (46% male, 86% Caucasian), latent variable FFM traits (using multiple‐informant reports) and aggregated cardiometabolic risk (indicators: insulin resistance, dyslipidemia, blood pressure, adiposity) were estimated using confirmatory factor analysis (CFA). The cardiometabolic factor was regressed on each personality factor or higher‐order trait. Cross‐sectional indirect effects via systemic inflammation, cardiac autonomic control, and physical activity were tested. CFA models confirmed the Stability “meta‐trait,” but not Plasticity. Lower Stability was associated with heightened cardiometabolic risk. This association was accounted for by inflammation, autonomic function, and physical activity. Among FFM traits, only Openness was associated with risk over and above Stability, and, unlike Stability, this relationship was unexplained by the intervening variables. A Stability meta‐trait covaries with midlife cardiometabolic risk, and this association is accounted for by three candidate biological and behavioral factors.     

General Factors of Personality in Six Datasets and a Criterion‐Related Validity Study at the Netherlands Armed Forces

Several papers showed that a general factor occupies the top of the hierarchical structure of personality, the so‐called General Factor of Personality (GFP). The first question is whether the GFP behaves similar to the general factor of mental ability (g), in that GFP scores from different personality questionnaires correlate highly. The second question is whether the GFP is related to real‐life outcomes. In six large datasets (total N=21,754) collected in the Netherlands armed forces, the GFPs extracted from six personality questionnaires generally showed high degrees of correlation suggesting they measure the same construct. Moreover, GFP was related to drop‐out from military training. This evidence strengthens the view that the GFP is a substantive construct with practical relevance.     

Multilevel Mixture Factor Models

Factor analysis is a statistical method for describing the associations among sets of observed variables in terms of a small number of underlying continuous latent variables. Various authors have proposed multilevel extensions of the factor model for the analysis of data sets with a hierarchical structure. These Multilevel Factor Models (MFMs) have in common that—as in multilevel regression analysis—variation at the higher level is modeled using continuous random effects. In this article, we present an alternative multilevel extension of factor analysis which we call the Multilevel Mixture Factor Model (MMFM). It is based on the assumption that higher level units belong to latent classes that differ in terms of the parameters of the factor model specified for the lower level units. We demonstrate the added value of MMFM compared with MFM, both from a theoretical and applied perspective, and we illustrate the complementarity of the two approaches with an empirical application on students' satisfaction with the University of Florence. The multilevel aspect of this application is that students are nested within study programs, which makes it possible to cluster these programs based on their differences in students' satisfaction.