In one currently dominant view on personality, personality dimensions (e.g. extraversion) are causes of human behaviour, and personality inventory items (e.g. ‘I like to go to parties’ and ‘I like people’) are measurements of these dimensions. In this view, responses to extraversion items correlate because they measure the same latent dimension. In this paper, we challenge this way of thinking and offer an alternative perspective on personality as a system of connected affective, cognitive and behavioural components. We hypothesize that these components do not hang together because they measure the same underlying dimension; they do so because they depend on one another directly for causal, homeostatic or logical reasons (e.g. if one does not like people and it is harder to enjoy parties). From this ‘network perspective’, personality dimensions emerge out of the connectivity structure that exists between the various components of personality. After outlining the network theory, we illustrate how it applies to personality research in four domains: (i) the overall organization of personality components; (ii) the distinction between state and trait; (iii) the genetic architecture of personality; and (iv) the relation between personality and psychopathology. Copyright © 2012 John Wiley & Sons, Ltd.

Despite a wealth of research, the core features of psychopathy remain hotly debated.Using network analysis, an innovative and increasingly popular statistical tool, we mapped the network structure of psychopathy, as operationalized by the Psychopathy Checklist-Revised (PCL-R; Hare, 2003) in two large U.S. offender samples (n NIMH = 1559; n Wisconsin = 3954), and one large Dutch forensic psychiatric sample (n TBS = 1937). Centrality indices were highly stable within each sample, and indicated that Callousness/lack of empathy was the most central PCL-R item in the two U.S.samples, which aligns with classic clinical descriptions and prototypicality studies of psychopathy. The similarities across the U.S. samples offer some support regarding generalizability, but there were also striking differences between the U.S. samples and the Dutch sample, wherein the latter Callousnesss/lack of empathy was also fairly central but Irresponsibility and Parasitic Lifestyle were even more central. The findings raise the important possibility that network-structures do not only reflect the structure of the constructs under study, but also the sample from which the data derive. The results further raise the possibility of cross-cultural differences in the phenotypic structure of psychopathy, PCL-R measurement variance, or both.Network analyses may help elucidate the core characteristics of psychopathological constructs, including psychopathy, as well as provide a new tool for assessing measurement invariance across cultures.

Problems associated with Autism Spectrum Disorder (ASD) occur frequently in the general population and often co-occur with problems in other domains of psychopathology. In the research presented here these co-occurrence patterns were investigated by integrating a dimensional approach to ASDs into the more general dimensional framework of internalizing and externalizing psychopathology. Factor Analysis was used to develop hierarchical and bi-factor models covering multiple domains of psychopathology in three measurement waves of a longitudinal general population sample (N = 2,230, ages 10-17, 50.8% female). In all adequately fitting models, autism related problems were part of a specific domain of psychopathology that could be distinguished from the internalizing and externalizing domains. Optimal model fit was found for a bi-factor model with one non-specific factor and four specific factors related to internalizing, externalizing, autism spectrum problems and problems related to attention and orientation. Autism-related problems constitute a specific domain of psychopathology that can be distinguished from the internalizing and externalizing domains. In addition, the co-occurrence patterns in the data indicate the presence of a strong general factor.

Demoralization, a nonspecific unpleasant state that is common in clinical practice, has been identified as a potential source of nonspecificity in the assessment of personality and psychopathology. The aim of this research was to distinguish between Demoralization and specific personality traits in a widely used measure of personality: the Neuroticism-Extraversion-Openness Personality Inventory-Revised (NEO-PI-R). NEO-PI-R and Minnesota Multiphasic Personality Inventory-2 questionnaires were completed by 278 patients of a specialized clinic for personality disorders in The Netherlands. Furthermore, a replication sample was used consisting of 405 patients from the same institution who completed NEO-PI-R questionnaires, as well. A measure of Demoralization was derived (NEOdem, a NEO-PI-R-based Demoralization scale) using factor analytic techniques. Results indicated that the Demoralization Scale scores were reliable and showed expected patterns of convergence and divergence with conceptually relevant Minnesota Multiphasic Personality Inventory-2-RF scales. When items contributing to Demoralization-related variance were removed from the NEO-PI-R scales, increased specificity was notable with regard to external correlates. These results provide supportive evidence for the validity and heuristic potential of distinguishing between Demoralization and specific personality traits within the NEO-PI-R.