Looking beyond the Big Five: A selective review of alternatives to the Big Five model of personality

Is it time to replace the Big Five personality model? Factorial structure of the NEO PI-R in a community sample of Spanish adults

Recent studies have revived the issue of whether the five-factor personality model or Big Five is the most valid to summarize the most relevant personality traits or whether, on the contrary, the basic structure of personality traits would better fit a six-factor model such as the HEXACO model: Honesty-Humility (H), Emotionality (E), Extraversion (X), Agreeableness (A), Conscientiousness (C), and Openness to Experience (O). In a Spanish community sample of 682 adults, the factorial structure of the 30 facets of the NEO-Revised Personality Inventory (NEO PI-R) and its 16 facets common to the HEXACO model was analyzed. In two subsamples of participants, the internal structure of the NEO PI-R, of 30 and 16 facets, fit the five-factor Big Five model better than the six-factor HEXACO model. In addition, the internal 30-facet structure of the NEO-PI-R replicated that obtained in the original US validation and those previously obtained in Spain, although the latter used different participant samples (people evaluated in personnel selection processes, university students). These results suggest that, at least in Spain, the five-factor personality model or Big Five is still the most valid taxonomy of personality traits.

A Richer Vocabulary of Chinese Personality Traits: Leveraging Word Embedding Technology for Mining Personality Descriptors

This study uses a data-driven approach to mine the distribution of personality traits among Chinese people in the Chinese social context. Based on the hypothesis of personality lexicology, word embedding technology was employed in machine learning to mine personality vocabulary from Tencent's word embedding database. More than 10,000 Chinese personality descriptors were extracted and analyzed using Gaussian Mixture Model Cluster and Hierarchical clustering analysis. The data was collected from 658 Chinese people randomly from all parts of China through an online questionnaire method. The results reveal six personality traits in the Chinese context, expanding the personality thesaurus and providing examples to illustrate each trait. The findings coincide with previous research on the five-factor model, which partially describes the personality traits of Chinese people, but does not offer a complete explanation of their typical social behavior patterns. Additionally, the study supports the notion of cultural particularity in personality traits. The approach used in this study offers a richer personality vocabulary than traditional personality mining methods, and word embedding technology captures richer semantic information in Chinese. The six Chinese personality traits identified in this study will also be used to explore how to quantify and evaluate personality traits based on word embedding and personality descriptors.

Association between the Big Five personality traits and suicide-related behaviors in Japanese institutionalized youths

Aim

Inmates in correctional institutions experience higher rates of suicide attempt (SA), suicidal ideation (SI), and nonsuicidal self-injury (NSSI) than the general population. This study aimed to examine the association between the Big Five personality traits and suicide-related behavior, and to estimate the prevalence rate of such behaviors among Japanese institutionalized youth.

Methods

The participants were 436 youths who had been admitted to four juvenile classification homes (JCHs) between September 2021 and March 2023; they were asked to respond to a self-report questionnaire after obtaining informed consent.

Results

A total of 8.1% and 19.3%, 29.4% and 44.7%, and 46.3% and 75.3% of males and females had experienced SA, SI, and NSSI in their lifetime, respectively. Females reported significantly higher instances of suicide-related behaviors than males considering all suicide-related behaviors. Logistic regression analyses revealed that neuroticism significantly increased the odds ratios for SA, SI, and NSSI on controlling for sex, age, and number of admissions to JCHs. For NSSI, the odds ratio for agreeableness was significantly lower than 1, indicating a lower probability of NSSI.

Conclusion

The findings of our study demonstrate that neuroticism, one of the Big Five traits, was consistently and significantly associated with all suicide-related behaviors, including SA, SI, and NSSI, among youth offenders, while agreeableness was found as a protective factor only against NSSI. The results of this study might help correctional officers identify justice-involved youth at higher risk for suicide and allow the development of early interventions to prevent suicide.

Mapping the terrain: a scoping review of empirical studies on the big five personality traits and QoL in China

The relationship between personality traits and Quality of Life (QoL) has garnered increasing scholarly attention, particularly within the context of China. This scoping review synthesizes existing literature on the connection between the Big Five personality traits (Openness, Conscientiousness, Extraversion, Agreeableness, and Neuroticism) and QoL among the Chinese population. The review explores correlations, measurement instruments, and theoretical frameworks employed in these studies. The study's significance lies in the profound implications for healthcare policies, organizational behavior, and social welfare programs in China, where rapid social and economic changes impact well-being. Investigating personality traits' impact on QoL can inform tailored interventions benefiting diverse Chinese subpopulations. This review addresses three primary research questions: (1) How do the Big Five personality traits correlate with QoL in different Chinese subpopulations, and what are the mediating or moderating factors? (2) What instruments assess these traits and QoL in the Chinese cultural context, and how are they validated? (3) What theoretical or disciplinary frameworks guide this research in China? Following a systematic PRISMA-ScR framework and a customized "C-BFQLC" protocol, the study identified 170 relevant documents. After rigorous screening, ten studies met the inclusion criteria, constituting 5.03% of the initial records. This scoping review critically examines the interplay between the Big Five personality traits and QoL in China, a context marked by rapid socioeconomic changes and cultural diversity. Employing a systematic approach guided by the PRISMA-ScR framework and our unique 'C-BFQLC' protocol, we meticulously analyzed 170 documents, selecting nine that met our rigorous inclusion criteria. Despite the emerging nature of this research area in the Chinese context, our study reveals significant insights into how individual personality traits influence various dimensions of well-being. The implications of these findings are profound, extending beyond academic discourse to inform healthcare policies, organizational behavior, and social welfare programs in China. Our review not only offers a comprehensive synthesis of the current research landscape but also identifies critical gaps in the literature. It emphasizes the urgent need for further culturally nuanced research to understand the complex dynamics of personality traits and QoL in China. This work lays a foundational framework for future investigations and the development of tailored interventions aimed at enhancing the well-being of diverse Chinese populations, including the elderly, people with disabilities, and specific occupational groups.

Childhood personality and academic performance: A sibling fixed-effects study

OBJECTIVE

This study investigated the associations between personality traits at age 8 and academic performance between ages 10 and 14, controlling for family confounds.

BACKGROUND

Many studies have shown links between children's personality traits and their school performance. However, we lack evidence on whether these associations remain after genetic and environmental confounders are accounted for.

METHOD

Sibling data from the Norwegian Mother and Child Cohort Study (MoBa) were used (n = 9701). First, we estimated the overall associations between Big Five personality traits and academic performance, including literacy, numeracy, and foreign language. Second, we added sibling fixed effects to remove unmeasured confounders shared by siblings as well as rating bias.

RESULTS

Openness to Experience (between-person β = 0.22 [95% CI: 0.21-0.24]) and Conscientiousness (between-person β = 0.18 [95% CI 0.16-0.20]) were most strongly related to educational performance. Agreeableness (between-person β = 0.06 [95% CI -0.08-0.04]) and Extraversion (between-person β = 0.02 [95% CI 0.00-0.04]) showed small associations with educational performance. Neuroticism had a moderate negative association (between-person β = -0.14 [95% CI -0.15-0.11]). All associations between personality and performance were robust to confounding: the within-family estimates from sibling fixed-effects models overlapped with the between-person effects. Finally, childhood personality was equally predictive of educational performance across ages and genders.

CONCLUSIONS

Although family background is influential for academic achievement, it does not confound associations with personality. Childhood personality traits reflect unbiased and consistent individual differences in educational potential.

Understanding the effect of proactive personality and perceived consumer effectiveness on low-carbon travel intention

Choosing low-carbon transportation is an effective strategy for mitigating carbon emissions. This study utilized the Theory of Planned Behavior (TPB) framework to investigate the influences of proactive personality and perceived consumer effectiveness on low-carbon travel intention. By surveying urban residents, we examined the effects of subjective norm, behavioral attitude, perceived behavioral control, proactive personality, and perceived consumer effectiveness on low-carbon travel intention. The findings indicated that subjective norm, behavioral attitude, perceived behavioral control, proactive personality, and perceived consumer effectiveness have positive impacts on low-carbon travel intention. Notably, subjective norms have the greatest influence on behavioral intention, followed by proactive personality, while perceived consumer effectiveness has the least impact. Furthermore, this study identified attitude and perceived behavioral control as mediating factors between proactive personality, perceived consumer effectiveness, and low-carbon travel intentions. These findings reaffirmed the universal applicability of the TPB in individual decision-making contexts. The results also suggested that to promote low-carbon travel, it is crucial to not only focus on the social aspects of urban residents but also leverage the potential of individuals with a proactive personality.

Status-impact assessment: is accuracy linked with status motivations?

Status hierarchies are ubiquitous across cultures and have been over deep time. Position in hierarchies shows important links with fitness outcomes. Consequently, humans should possess psychological adaptations for navigating the adaptive challenges posed by living in hierarchically organised groups. One hypothesised adaptation functions to assess, track, and store the status impacts of different acts, characteristics and events in order to guide hierarchy navigation. Although this status-impact assessment system is expected to be universal, there are several ways in which differences in assessment accuracy could arise. This variation may link to broader individual difference constructs. In a preregistered study with samples from India (N = 815) and the USA (N = 822), we sought to examine how individual differences in the accuracy of status-impact assessments covary with status motivations and personality. In both countries, greater overall status-impact assessment accuracy was associated with higher status motivations, as well as higher standing on two broad personality constructs: Honesty-Humility and Conscientiousness. These findings help map broad personality constructs onto variation in the functioning of specific cognitive mechanisms and contribute to an evolutionary understanding of individual differences.

Dimensional models of personality disorders: Challenges and opportunities

Categorical models of personality disorders have been beneficial throughout psychiatric history, providing a mechanism for organizing and communicating research and treatment. However, the view that individuals with personality disorders are qualitatively distinct from the general population is no longer tenable. This perspective has amassed steady criticism, ranging from inconsequential to irreconcilable. In response, stronger evidence has been accumulated in support of a dimensional perspective that unifies normal and pathological personality on underlying trait continua. Contemporary nosology has largely shifted toward this dimensional perspective, yet broader adoption within public lexicon and routine clinical practice appears slow. This review focuses on challenges and the related opportunities of moving toward dimensional models in personality disorder research and practice. First, we highlight the need for ongoing development of a broader array of measurement methods, ideally facilitating multimethod assessments that reduce biases associated with any single methodology. These efforts should also include measurement across both poles of each trait, intensive longitudinal studies, and more deeply considering social desirability. Second, wider communication and training in dimensional approaches is needed for individuals working in mental health. This will require clear demonstrations of incremental treatment efficacy and structured public health rebates. Third, we should embrace cultural and geographic diversity, and investigate how unifying humanity may reduce the stigma and shame currently generated by arbitrarily labeling an individual's personality as normal or abnormal. This review aims to organize ongoing research efforts toward broader and routine usage of dimensional perspectives within research and clinical spaces.

Premorbid Personality Traits as Risk Factors for Behavioral Addictions: A Systematic Review of a Vulnerability Hypothesis

The debate on personality structure and behavioral addictions is an outstanding issue. According to some authors, behavioral addictions could arise from a premorbid personality, while for others, it could result from a pathological use of technological tools. The current study aims to investigate whether, in the latest literature, personality traits have been identified as predictors of behavioral addictions. A literature search was conducted under the PRISMA methodology, considering the most relevant studies of the five-factor model from the past 10 years. Overall, most studies on addiction, personality traits, and personality genetics proved that behavioral addiction may be an epiphenomenon of a pre-existing personality structure, and that it more easily occurs in vulnerable subjects with emotional instability, negative affects, and unsatisfactory relationships with themselves, others, and events. Such neurotic personality structure was common to any addictive behavior, and was the main risk factor for both substance and behavioral addictions. Therefore, in clinical and educational contexts, it becomes crucial to primarily focus on the vulnerability factors, at-risk personality traits, and protective and moderating traits such as extroversion, agreeableness, conscientiousness, and openness to experience; meanwhile, treatment of behavioral addictions is frequently focused on overt pathological behaviors.

Exploring Factor Structures Using Variational Autoencoder in Personality Research

An accurate personality model is crucial to many research fields. Most personality models have been constructed using linear factor analysis (LFA). In this paper, we investigate if an effective deep learning tool for factor extraction, the Variational Autoencoder (VAE), can be applied to explore the factor structure of a set of personality variables. To compare VAE with LFA, we applied VAE to an International Personality Item Pool (IPIP) Big 5 dataset and an IPIP HEXACO (Humility-Honesty, Emotionality, Extroversion, Agreeableness, Conscientiousness, Openness) dataset. We found that LFA tends to break factors into ever smaller, yet still significant fractions, when the number of assumed latent factors increases, leading to the need to organize personality variables at the factor level and then the facet level. On the other hand, the factor structure returned by VAE is very stable and VAE only adds noise-like factors after significant factors are found as the number of assumed latent factors increases. VAE reported more stable factors by elevating some facets in the HEXACO scale to the factor level. Since this is a data-driven process that exhausts all stable and significant factors that can be found, it is not necessary to further conduct facet level analysis and it is anticipated that VAE will have broad applications in exploratory factor analysis in personality research.

Predicting Construction Workers’ Intentions to Engage in Unsafe Behaviours Using Machine Learning Algorithms and Taxonomy of Personality

Dynamic environmental circumstances can sometimes be incompatible with proactive human intentions of being safe, leading individuals to take unintended risks. Behaviour predictions, as performed in previous studies, are found to involve environmental circumstances as predictors, which might thereby result in biased safety conclusions about individuals’ inner intentions to engage in unsafe behaviours. This research calls attention to relatively less-understood worker intentions and provides a machine learning (ML) approach to help understand workers’ intentions to engage in unsafe behaviours based on the workers’ inner drives, i.e., personality. Personality is consistent across circumstances and allows insight into one’s intentions. To mathematically develop the approach, data on personality and behavioural intentions was collected from 268 workers. Five ML architectures—backpropagation neural network (BP-NN), decision tree, support vector machine, k-nearest neighbours, and multivariate linear regression—were used to capture the predictive relationship. The results showed that BP-NN outperformed other algorithms, yielding minimal prediction loss, and was determined to be the best approach. The approach can generate quantifiable predictions to understand the extent of workers’ inner intentions to engage in unsafe behaviours. Such knowledge is useful for understanding undesirable aspects in different workers in order to recommend suitable preventive strategies for workers with different needs.

A Tri-Directional Examination of Parental Personality, Parenting Behaviors, and Contextual Factors in Influencing Adolescent Behavioral Outcomes

Links between parental personality, parenting, and adolescent behavior have been well established. However, extant research is limited by the sole focus on parental Big Five personality, and not taking home and family context into account. These gaps were addressed in two studies. In study 1, context, parental personality, and their interactions were examined as predictors of parenting in separate mother and father models (parents only). In study 2, context, parental personality, and parenting were examined as predictors of adolescent behavioral outcomes (parent–adolescent dyads). Parents (N = 283, 45.6% mothers, Mage = 45.51 years) completed assessments of socioeconomic status (SES), adverse childhood experiences (ACEs), personality (Big Five, Dark Triad), and parenting. Adolescents (N = 257, 51.4% female, Mage = 13.65 years) completed an assessment of behavior. Parent Dark Triad domains explained more variance in parental warmth and hostility than the Big Five, but equivalent variance in adolescent behavior. SES interacted with maternal personality, whereas ACEs interacted with paternal personality, to predict parenting behavior. The results showcase the importance of assessing a wider spectrum of parental personality, and examining contextual factors, in affecting adolescent development.

The Nexus Between the Big Five Personality Traits Model of the Digital Economy and Blockchain Technology Influencing Organization Psychology

The basic aim of the study was to understand the role of the Big Five model of personality in predicting emotional intelligence and consequently in triggering the entrepreneurial behavior of the employees. The emotional intelligence of the individuals plays a very important role in decision making, enhancement of quality of living, and many other social realms. Hence, the intelligent use of emotions can make or break an individual’s future considering their attitude toward exploiting the entrepreneurial opportunities available. This study has measured the impact of personality traits on emotional intelligence and EI’s role in digital entrepreneurial behavior. The population used in this study was the middle management employees in the corporate sector of the mainland in China. The sample size taken in this study was 260 and selected through convenient sampling. The data was collected through a structured questionnaire measuring each variable. The data collected was employed to SmartPLS 3.3 for analyzing through structural equation modeling to measure the hypotheses. The study has found the partial effect of the Big Five model of personality on emotional intelligence, which significantly predicted the digital entrepreneurial behavior of the employees. The organizations can use the study findings to anticipate the employees’ possible prospects and endeavors regarding their digital entrepreneurial behaviors.

CyberGenomics: Application of Behavioral Genetics in Cybersecurity

Cybersecurity (CS) is a contemporary field for research and applied study of a range of aspects from across multiple disciplines. A cybersecurity expert has an in-depth knowledge of technology but is often also recognized for the ability to view technology in a non-standard way. This paper explores how CS specialists are both a combination of professional computing-based skills and genetically encoded traits. Almost every human behavioral trait is a result of many genome variants in action altogether with environmental factors. The review focuses on contextualizing the behavior genetics aspects in the application of cybersecurity. It reconsiders methods that help to identify aspects of human behavior from the genetic information. And stress is an illustrative factor to start the discussion within the community on what methodology should be used in an ethical way to approach those questions. CS positions are considered stressful due to the complexity of the domain and the social impact it can have in cases of failure. An individual risk profile could be created combining known genome variants linked to a trait of particular behavior using a special biostatistical approach such as a polygenic score. These revised advancements bring challenging possibilities in the applications of human behavior genetics and CS.

Individual differences in need satisfaction and intentions to vote for specific political parties – results from Germany

Understanding the psychological basis of individuals' voting intentions is of tremendous importance because voting for specific parties and politicians can influence political developments. In the present study associations of individuals’ satisfaction of each of Maslow’s five basic need categories with voting intentions were investigated in a German sample and these results were compared to results on associations between personality and voting intentions. An online survey was completed by N = 2593 (n = 1035 men) individuals. Participants provided information on socio-demographic characteristics, filled in the Need Satisfaction Inventory, the Big Five Inventory, and stated which of the major German parties they would vote for if general elections were held the following Sunday. Data were analyzed using the statistical software R and RStudio. Among others, it was found that higher satisfaction of physiological needs and higher satisfaction of safety and security needs were associated with intentions to vote for the currently governing party alliance, the CDU/CSU, versus for the right-wing AfD. Regarding personality, among others Openness was positively associated with intentions to vote for nearly every party (except the CDU/CSU) versus for the AfD. Effect sizes of associations were overall rather small; generally speaking, those related to the Need Satisfaction Inventory were even slightly smaller than those found for personality traits. The present results indicate that other factors aside from needs and personality must be considered to understand voting. Therefore, this study sets a starting point for further investigations to replicate and expand the present findings.

Personality trait of conscientiousness impact on tacit knowledge sharing: the mediating effect of eagerness and subjective norm

Purpose

This study aims to examine psychological mechanisms underlying tacit knowledge-sharing behaviours. The personality trait of conscientiousness is tested in relation to knowledge sharing, and the effect of eagerness and subjective norm on the intention to share is measured in the context of local and multinational knowledge-intensive enterprises in Croatia.

Design/methodology/approach

The quantitative study was conducted on a sample of 288 employees of small and medium-sized companies working on knowledge-intensive tasks. The purposive sampling technique and a survey strategy were used in the study. Organizational affiliation, as it was presumed that these individuals possess a higher degree of tacit knowledge. The data collection was conducted in October 2019. Respondents worked in science and technology companies in Croatia on assignments involving information technology, electronics, petrochemicals, medicine and biochemistry. Statistical product and service solutions analysis of a moment structures software was used to perform confirmatory factor analysis and structural equation modelling.

Findings

The findings suggest that the personality trait of conscientiousness has a positive impact on tacit knowledge sharing behaviour. An attitude of eagerness and subjective norm were also confirmed as predictors of tacit knowledge sharing behaviour. Furthermore, conscientiousness influences the eagerness to share knowledge. A significant association between subjective norm and conscientiousness was also established. Finally, the mediating effects were identified, indicating that subjective norm and eagerness mediate the relationship between conscientiousness and tacit knowledge sharing.

Practical implications

Explaining the relationship between personality and attitude in the context of knowledge sharing will result in a better understanding of factors that should be nurtured within individuals. Accordingly, distinct management initiatives are to be developed to suit these factors. Furthermore, to intensify the knowledge exchange when working on knowledge-intensive tasks of significant economic value, organizations tailor a more particularistic application to suit the individual in the domain of leadership, staffing decisions, work organization and incentive systems.

Originality/value

This study provides an in-depth analysis and theoretical understanding of factors salient for knowledge-sharing behaviour. The authors provide an overview of how knowledge sharing evolves during social interaction through intensive problem-solving sessions and teamwork. The authors render the explanation on how the personality trait of conscientiousness, conjoint with the attitude of eagerness to share know-how in the expert surrounding, is conducive to the generation of tacit knowledge sharing. Underpinning this study are employees’ psychological motives and internal drives to communicate individual cognitive capital outweighing the potential negative consequences, such as losing the competitive advantage over the colleagues.

On the Comparability of Basic Personality Models: Meta-Analytic Correspondence, Scope, and Orthogonality of the Big Five and HEXACO Dimensions

Models of basic personality structure are among the most widely used frameworks in psychology and beyond, and they have considerably advanced the understanding of individual differences in a plethora of consequential outcomes. Over the past decades, two such models have become most widely used: the Five Factor Model (FFM) or Big Five, respectively, and the HEXACO Model of Personality. However, there is no large-scale empirical evidence on the general comparability of these models. Here, we provide the first comprehensive meta-analysis on (a) the correspondence of the FFM/Big Five and HEXACO dimensions, (b) the scope of trait content the models cover, and (c) the orthogonality (i.e., degree of independence) of dimensions within the models. Results based on 152 (published and unpublished) samples and 6,828 unique effects showed that the HEXACO dimensions incorporate notable conceptual differences compared to the FFM/Big Five dimensions, resulting in a broader coverage of the personality space and less redundancy between dimensions. Moreover, moderator analyses revealed substantial differences between operationalizations of the FFM/Big Five. Taken together, these findings have important theoretical and practical implications for the understanding of basic personality dimensions and their assessment.

They Saw It Coming: Rising Trends in Depression, Anxiety, and Suicidality in Creative Students and Potential Impact of the COVID-19 Crisis

Previous research has established that creative adolescents are generally low in neuroticism and as well-adjusted as their peers. From 2006 to 2013, data from cohorts of creative adolescents attending a counseling laboratory supported these results. Clinical findings of increased anxiety, depression, and suicidality among creative students in 2014 led the researchers to create 3 studies to explore these clinical findings. Once artifactual causes of these changes were ruled out, a quantitative study was conducted. Study 1, an analysis of mean differences of pre-2014 and post-2014 cohorts showed that post-2014 cohorts scored significantly higher in Neuroticism, Openness to Experience, and Conscientiousness and lower in Extraversion on Big 5 inventories. Regression analyses suggested that while Neuroticism was associated with gender, Conscientiousness and Grade Point Average for the earlier group, Neuroticism in the post 2014 groups was related to complex interplay of all personality dynamics except Agreeableness. In the qualitative Study 2, focus groups of 6–10 students, for a total of 102 participants were queried about the reasons they perceived for increased anxiety and depression in creative students. Increased achievement pressures and awareness of environmental and social problems were major sources of external stressors; perfectionism and desire to fulfill expectations of others were the primary sources of internal stress. The authors suggest that creative students' openness to experience and advanced knowledge made it possible for these students to see the potential for environmental and social crises and respond to their inability to solve these problems with anxiety and depression. Study 3 was a qualitative study that followed up 19 participants from the post-2014 cohort to explore the impact of the COVID-19 pandemic on mental health and creativity. While the majority perceived a negative effect of the pandemic on their mental health, most also produced a surprising variety of creative works during that time. In conclusion, rapid changes in the lives of creative adolescents since 2014 suggest that scholars focus on current cohorts and the ways in which adolescent personality is shaped by internal expectation and external pressures and global events. Despite the pandemic, creative young people continued to create.