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Normative and pathological personality traits have rarely been integrated into a joint large-scale structural analysis with psychiatric disorders, although a recent study suggested they entail a common individual differences continuum. We explored the joint factor structure of 11 psychiatric disorders, five personality-disorder trait domains (DSM-5 Section III), and five normative personality trait domains (the 'Big Five') in a population-based sample of 2796 Norwegian twins, aged 19‒46. Three factors could be interpreted: (i) a general risk factor for all psychopathology, (ii) a risk factor specific to internalizing disorders and traits, and (iii) a risk factor specific to externalizing disorders and traits. Heritability estimates for the three risk factor scores were 48% (95% CI 41‒54%), 35% (CI 28‒42%), and 37% (CI 31‒44%), respectively. All 11 disorders had uniform loadings on the general factor (congruence coefficient of 0.991 with uniformity). Ignoring sign and excluding the openness trait, this uniformity of factor loadings held for all the personality trait domains and all disorders (congruence 0.983). Based on our findings, future research should investigate joint etiologic and transdiagnostic models for normative and pathological personality and other psychopathology.

PurposeThe literature considers the big five personality traits and entrepreneurial self-efficacy (ESE) to be important individual-level factors that determine entrepreneurial intention. However, little is known about the profiles of personal characteristics of individuals who express a high level of entrepreneurial intention. The purpose of this paper is to carry out a comparative analysis of personal characteristics that contribute to new business start-up intention.Design/methodology/approachUsing survey data from two samples, fuzzy set qualitative comparative analysis (fsQCA) was performed to extract patterns of personal characteristics (i.e. the big five personality traits and ESE) that impact entrepreneurial intention.FindingsThe outcomes of the analyses demonstrate that a high level of entrepreneurial intention can be realized through multiple configurations of the big five personality traits and ESE.Practical implicationsThis paper can inform practice on entrepreneurship education. Specifically, the paper includes implications for the development of ESE, and for understanding multiple configurations of personal characteristics that lead to a high level of entrepreneurial intention.Originality/valueThis paper addresses an identified need to understand how personal characteristics operate conjointly and among individuals.

Although there has been increasing interest in dark personality traits in the organizational sciences, these characteristics remain relatively understudied and somewhat misunderstood. The present manuscript aims to clarify some of the issues surrounding dark personality traits by discussing the history of dark personality traits, how they relate to normal personality traits, their relative importance as determinants of organizational outcomes, and measurement issues surrounding the assessment of these characteristics. We will then discuss potential future directions for research investigating the causes and consequences of these traits as well as providing guidance on the implementation of dark personality assessment in the workplace for selection and training.

Using data from 138 independent samples, we meta-analytically examined three research questions concerning the roles of personality and network position in organizations. First, how do different personality characteristics—self-monitoring and the Big Five personality traits—relate to indegree centrality and brokerage, the two most studied structurally advantageous positions in organizational networks? Second, how do indegree centrality and brokerage compare in explaining job performance and career success? Third, how do these personality variables and network positions relate to work outcomes? Our results show that self-monitoring predicted indegree centrality (across expressive and instrumental networks) and brokerage (in expressive networks) after controlling for the Big Five traits. Self-monitoring, therefore, was especially relevant for understanding why people differ in their acquisition of advantageous positions in social networks. But the total variance explained by personality ranged between 3% and 5%. Surprisingly, we found that indegree centrality was more strongly related to job performance and career success than brokerage. We also found that personality predicted job performance and career success above and beyond network position and that network position partially mediated the effects of certain personality variables on work outcomes. This paper provides an integrated view of how an individual’s personality and network position combine to influence job performance and career success.

The automatic assessment of psychological traits from digital footprints allows researchers to study psychological traits at unprecedented scale and in settings of high ecological validity. In this research, we investigated whether spending records—a ubiquitous and universal form of digital footprint—can be used to infer psychological traits. We applied an ensemble machine-learning technique (random-forest modeling) to a data set combining two million spending records from bank accounts with survey responses from the account holders (N = 2,193). Our predictive accuracies were modest for the Big Five personality traits (r = .15, corrected ρ = .21) but provided higher precision for specific traits, including materialism (r = .33, corrected ρ = .42). We compared the predictive accuracy of these models with the predictive accuracy of alternative digital behaviors used in past research, including those observed on social media platforms, and we found that the predictive accuracies were relatively stable across socioeconomic groups and over time.

PurposeThe main objective is to investigate the effects of antecedents of word-of-mouth (WOM) towards sustainable fashion, using the Personality Traits theory. More specifically, this study wants to examine the impact of the Big Five personality traits on social media activities, which could affect eco-friendly behaviour and environmental concerns for fashion production. This impact is influenced by the use of WOM on sustainability in the fashion industry.Design/methodology/approachThe partial least squares structural equation modelling (PLS SEM) technique is used to evaluate the internal and external measurement model with a sample size of 272.FindingsThe three most active personality traits on social media are extraversion, openness to experience and agreeableness. Additionally, the active use of social media has a positive impact on the optimisation of users' eco-friendly behaviour and an increase in users' concerns for fashion production. Eco-friendly behaviour and environmental concerns for fashion production are important factors that lead to the spread of WOM.Originality/valueThis study contributes to the existing literature by evaluating the effects of the Big Five personality traits on using social networking and how will this improve the creation of WOM towards sustainability. This study is among the several scientific studies which combine the theory of Big Five personality traits with social networking, green behaviour and the WOM in a sustainability context.

Released in 2012 as a free, easily administered measure of personality pathology domains and traits as described in the DSM-5 Alternative Model for Personality Disorders, the Personality Inventory for DSM-5 (PID-5) has spawned interest—and a considerable amount of research—since its publication. Rather than trying to match an individual's personal experience to preestablished diagnostic categories, use of the PID-5 in assessment calls for something of a paradigm shift—developing a profile unique to each patient and their experiences and behaviors. This new book delves into the background of the PID-5 and provides clinical and research guidance on its application. After reviewing the blossoming literature on the PID-5 and evidence for its use, the authors examine • The validity of the PID-5 in different populations, including adults, children, and non-U.S. populations • Special applications of the PID-5, including its relation to ICD-11 and use in forensic constructs • The relationship of the PID-5 with other measures, such as the Five Factor Model measures and the Personality Assessment Inventory • The role of the PID-5 in developing tailored interventions and prevention strategies, both psychotherapeutic and pharmacological Standout features of this guide include numerous and easily referenced tables throughout, clinical vignettes that help illustrate the PID-5 personality profiles, and an appendix with norms and scoring reference materials. Particularly useful for both clinical psychologists and research psychiatrists, Understanding the Personality Inventory for DSM-5 (PID-5) is a concise, convenient, and indispensable resource for all those interested in an individualized approach to the management and treatment of personality pathologies.

This study investigated the relationships between active, problem-focused, and maladaptive coping with stress during the Coronavirus outbreak, the Big Five personality traits, and social support among Israeli-Palestinian college students ( n  = 625). Emotion-focused coping negatively correlated with social support, openness, extraversion, conscientiousness, and agreeableness, while it positively correlated with neuroticism. On the other hand, problem-focused coping was found to positively correlate with social support, openness, extraversion, conscientiousness, and agreeableness, but negatively correlate with neuroticism. Thus, positive social support may increase one’s ability to cope actively, adaptively, and efficiently. In addition, Israeli-Palestinian college students high in openness, extraversion, agreeableness, and conscientiousness tend to use active problem-focused coping while those high in neuroticism tend to use maladaptive emotion-focused coping.

This study aims to demonstrate that Large Language Models (LLMs) can empower research on the evolution of human behavior, based on evolutionary game theory, by using an evolutionary model positing that instructing LLMs with high-level psychological and cognitive character descriptions enables the simulation of human behavior choices in game-theoretical scenarios. As a first step towards this objective, this paper proposes an evolutionary model of personality traits related to cooperative behavior using a large language model. In the model, linguistic descriptions of personality traits related to cooperative behavior are used as genes. The deterministic strategies extracted from LLM that make behavioral decisions based on these personality traits are used as behavioral traits. The population is evolved according to selection based on average payoff and mutation of genes by asking LLM to slightly modify the parent gene toward cooperative or selfish. Through experiments and analyses, we clarify that such a model can indeed exhibit evolution of cooperative behavior based on the diverse and higher-order representation of personality traits. We also observed repeated intrusion of cooperative and selfish personality traits through changes in the expression of personality traits. The words that emerged in the evolved genes reflected the behavioral tendencies of their associated personalities in terms of semantics, thereby influencing individual behavior and, consequently, the evolutionary dynamics.

The 11th revision of the World Health Organization (WHO) International Classification of Diseases (ICD-11) includes a fundamentally new approach to Personality Disorders (PD). ICD-11 is expected to be implemented first in European countries before other WHO member states. The present paper provides an overview of this new ICD-11 model including PD severity classification, trait domain specifiers, and the additional borderline pattern specifier. We discuss the perceived challenges and opportunities of using the ICD-11 approach with particular focus on its continuity and discontinuity with familiar PD categories such as avoidant PD and narcissistic PD. The advent of the ICD-11 PD classification involves major changes for health care workers, researchers, administrators, and service providers as well as patients and families involved. The anticipated challenges and opportunities are put forward in terms of specific unanswered questions. It is our hope that these questions will stimulate further research and discussion among researchers and clinicians in the coming years.