This review examines the neural correlates of Gray's model (Gray and McNaughton, 2000; McNaughton and Corr, 2004), supplemented by a fourth dimension: constraint (Carver, 2005). The purpose of this review is to summarize findings from fMRI studies that tap on neural correlates of personality aspects in healthy subjects, in order to provide insight into the neural activity underlying human temperament. BAS-related personality traits were consistently reported to correlate positively to activity of the ventral and dorsal striatum and ventral PFC in response to positive stimuli. FFFS and BIS-related personality traits are positively correlated to activity in the amygdala in response to negative stimuli. There is limited evidence that constraint is associated with PFC and ACC activity. In conclusion, functional MRI research sheds some light on the specific neural networks underlying personality. It is clear that more sophisticated task paradigms are required, as well as personality questionnaires that effectively differentiate between BAS, FFFS, BIS, and constraint. Further research is proposed to potentially reveal new insight in the neural subsystems governing basic human behavior.

Personality reflects social, affective, and cognitive predispositions that emerge from genetic and environmental influences. Contemporary personality theories conceptualize a Big Five Model of personality based on the traits of neuroticism, extraversion, agreeableness, conscientiousness, and openness to experience. Starting around the turn of the millennium, neuroimaging studies began to investigate functional and structural brain features associated with these traits. Here, we present the first study to systematically evaluate the entire published literature of the association between the Big Five traits and three different measures of brain structure. Qualitative results were highly heterogeneous, and a quantitative meta-analysis did not produce any replicable results. The present study provides a comprehensive evaluation of the literature and its limitations, including sample heterogeneity, Big Five personality instruments, structural image data acquisition, processing, and analytic strategies, and the heterogeneous nature of personality and brain structures. We propose to rethink the biological basis of personality traits and identify ways in which the field of personality neuroscience can be strengthened in its methodological rigor and replicability.

Job burnout has been on the rise in the past decade, especially amongst the younger working generation. While work environmental aspects play an important role in predicting burnout, variations in personality traits are integral for understanding the syndrome ’ s risk factors, processes, and outcomes. This paper studies the complex interaction of personality factors on the one hand and work environment aspects on the other through the relatively novel adaptive causal network modelling paradigm. Due to the adaptive nature of the model, it can investigate the effects of changes in particular job demands and resources on the symptoms of burnout and their dependence on different personality traits. The model can also demonstrate how an individual ’ s personality traits, environmental perception, and burnout symptoms can adaptively be altered by individual therapy, in this case, mindfulness-based cognitive therapy. Using the dedicated software environment in MATLAB to simulate the designed adaptive causal network model, two main scenarios were explored, focusing on the neuroticism personality trait. The results demonstrate that neuroticism increases due to interpersonal conflict, indicating that neuroticism can be treated as an adaptive trait. Furthermore, when mindfulness-based cognitive therapy was introduced into the simulation, the likelihood of developing burnout decreased because the perception of the work environment was positively changed due to the therapy. This model contributes to the field of burnout modelling by repre- senting personality traits as adaptive factors that can be changed through individual interventions. More detailed research is needed to understand how organisational-level interventions can also impact burnout development through changes in environmental perception and personality.

The study of personalities is a major component of human psychology, and with an understanding of personality traits, practical applications can be used in various domains, such as mental health care, predicting job performance, and optimising marketing strategies. This study explores the prediction of Big Five personality trait scores from online comments using transformer-based language models, focusing on improving the model performance with a larger dataset and investigating the role of intercorrelations among traits. Using the PANDORA dataset from Reddit, the RoBERTa and BERT models, including both the base and large variants, were fine-tuned and evaluated to determine their effectiveness in personality trait prediction. Compared to previous work, our study utilises a significantly larger dataset to enhance the model’s generalisation and robustness. The results indicate that RoBERTa outperforms BERT across most metrics, with RoBERTa large achieving the best overall performance. In addition to evaluating the overall predictive accuracy, this study investigates the impact of intercorrelations among personality traits. A comparative analysis is conducted between a single-model approach, which predicts all five traits simultaneously, and a multiple-model approach, fine-tuning the models independently and each predicting a single trait. The findings reveal that the single-model approach achieves a lower RMSE and higher R2 values, highlighting the importance of incorporating trait intercorrelations in improving the prediction accuracy. Furthermore, RoBERTa large demonstrated a stronger ability to capture these intercorrelations compared to previous studies. These findings emphasise the potential of transformer-based models in personality computing and underscore the importance of leveraging both larger datasets and intercorrelations to enhance predictive performance.

We present Big5-Scaler, a prompt-based framework for conditioning large language models (LLMs) with controllable Big Five personality traits. By embedding numeric trait values into natural language prompts, our method enables fine-grained personality control without additional training. We evaluate Big5-Scaler across trait expression, dialogue generation, and human trait imitation tasks. Results show that it induces consistent and distinguishable personality traits across models, with performance varying by prompt type and scale. Our analysis highlights the effectiveness of concise prompts and lower trait intensities, providing a efficient approach for building personality-aware dialogue agents.

Agricultural economists are increasingly incorporating insights from psychology into their research to better understand farmers’ behavior. The Big Five model of personality is frequently used in psychological research. This paper aims at answering how and when researchers use the Big Five personality traits when focusing on farmers (research questions, measurement of personality traits). In addition, we analyze to what extent the Big Five personality traits contribute to explaining farmers’ behaviors and outcomes. To answer these research questions, we carry out systematic literature research guided by the PRISMA approach. We searched three databases (Web of Science, Scopus, PubMed) at the end of February 2022 and identified n = 36 eligible studies. We included studies, which were written in English, which focused on farmers, including primary data and measurements of the Big Five personality traits. This is the first systematic and comprehensive review of the role of the Big Five personality traits in farmers’ behavior. Our review shows an increase in interest in the farmers’ Big Five personality traits in the past years, most often incorporated in research conducted in Europe. By carrying out the main steps of content analysis, we develop a taxonomy, categorizing the research aims of the reviewed studies. We identify three main categories: well-being (human and animal), business (in a broad sense and in a narrow sense), and methodological aims. Overall, our review suggests that some personality traits are more important for understanding farmers’ behaviors and outcomes than others, depending on the context. Indeed, we were able to identify some patterns. For instance, our review shows that neuroticism is most often negatively related to measures of human well-being, or business development, whereas agreeableness supports non-technical skills and education. Openness and extraversion seem to be strong predictors of pro-environmental behavior, whereas conscientiousness tends to increase business performance. To assess the possible risk of bias in the reviewed studies, we included a quality discussion. We further discuss the limitations of our review and identify avenues for future research. To increase the review’s credibility, we pre-registered our procedure (INPLASY202230138, DOI: 10.37766/inplasy2022.3.0138).

In the context of user experience (UX) evaluation, stress detection is crucial for identifying user discomfort during interactions. This study introduces an innovative approach that uses Digital Twins (DTs) to generate synthetic user data, thereby improving training of stress detection models without requiring extensive user recruitment. The proposed approach involves creating DTs that replicate physiological signals. A comprehensive analysis was conducted using well-known machine learning models. The results demonstrate that DTs can effectively augment training data without compromising classification accuracy. More specifically, Random Forest classifier achieved an accuracy of 96.34% on real user data and 99.50% on the aggregated dataset (real + synthetic physiological data). Instead of using a baseline condition, we classified users as stress-prone or non-stress-prone based on their Emotional Stability scores. These findings underscore the potential of DTs for scalable, precise stress detection in UX context and pave the way for real-time, adaptive feedback systems.

The study of children's personality and its development has generated several theoretical models in psychology. In a developmental approach, Buss and Plomin elaborated a genetic model of temperament that involves four dimensions: emotionality (refers to the negative quality of the emotion and the intensity of the emotional reactions), activity (intensity and frequency of a person's energy output in motor movements and speech), sociability (search for social relationships and preference for activities with others) and shyness (behavioural inhibition and feelings of distress when in interaction with strangers). The psychobiological approach postulates a biological model of personality. Thus, in Gray's first model, there are two brain systems that explain behaviours: the Bbehavioural Activation System (BAS) related to impulsivity and the Behavioural Inhibition System (BIS) linked to anxiety. Finally, dispositional theories seek to identify functional units of the normal personality from the factorial approach. Accordingly, Barbaranelli et al. build a questionnaire, the big five questionnaire for children (BFQ-C), which is intended to estimate the emergence of five fundamental dimensions (energy/extraversion, agreeableness, conscientiousness, emotional instability and intellect/openness) in children from 8 to 18 years. The clinical study we will present concerns the personality of children suffering from attention-deficit hyperactivity disorder (ADHD). STUDY 1:In a first study, w

The purpose of this present study was to examine the relationship between Reinforcement Sensitivity Theory (RST) and academic achievement. Academic achievement is becoming more important in our increasingly competitive environment. Over the years, personality has been shown to play a large factor in academic achievement. However, while the relationship of academic achievement and personality has been researched using more well-known theories of personality such as the Big Five theory of personality, little attention has been paid to alternative theories, such as RST. This study proposes a theoretical model with indirect effects of Behavioral Activation System (BAS) and Behavioral Inhibition System (BIS) on academic achievement through self-efficacy and goal orientation. Ninety-nine first –year university students participated in an online study in laboratories under the supervision of a researcher. Participants completed r-RST, goal orientation, two academic performance tests (sample test questions), and self-efficacy measures. To elicit change in self-efficacy and academic performance, participants were randomly assigned to either positive or neutral feedback between two performance tests and self-efficacy measures. It was found that while r-BAS had no effect on academic performance, r-BIS was significantly associated with academic performance. Moreover, the indirect effect of r-BIS on academic performance through both mediators was significant. It was also found that feedba

This dissertation examines the nature of personality in terms of the temperament and character framework identified by Cloninger and colleagues (1 993). This model proposes that personality can be understood in terms of temperament, unlearnt, essentially biological traits, and character, socioculturally learnt traits that reflect the individual ' s goals and values. The nature of these higher order dimensions of personality i s such that temperament motivates action, while character, based on the salience of the situation, intervenes to produce behavioural responses that best suit the individual ' s goals and values (Cloninger et. al., 1993). Two studies were used to test this theory. The first study hypothesised that this model could be used to explain cross-situational variability that has been demonstrated to exist in self-reported personality data. To test this, 1 7 3 first year psychology students completed the Temperament and Character Inventory (TCI) , the Big Five Inventory (BFI), the BIS/BAS Scales (BB S ) , the Appetitive Motivation Scale (AMS) and the Dickman Impulsivity Inventory (DII) indicating whether the items reflected temperament or character, and how true each item was for them across the four situations of: in general, at home, at work and in a perfect world. The results failed to support the hypotheses. Firstly, there were very few significant differences in the number of participants who were able to conceptualise their own behaviour in line with the the

Multiple theories regarding vocational choice have suggested that personality may be meaningfully related to vocational interest and vocational self-efficacy (Barrick, Mount, & Gupta, 2003; Larson and Borgen, 2006; Larson, Rottinghaus, & Borgen, 2002; Nauta, 2007), as well as the underlying mechanism (Hansen et al., 2011). One limitation in the literature of understanding the linkages between personality traits and interest and self-efficacy may be that personality traits have only been conceptualized from two dominant models, namely the Big Five (Costa & McCrae, 1992) and the Big Three (Tellegen, 2000). As discussed by Larson (2011), the use of additional models of personality may lead to greater understanding of key factors of vocational interest and self-efficacy. Using the constructs of the behavioral activation system (BAS) and behavioral inhibition system (BIS) as defined by Gray’s (1990) Reinforcement Sensitivity Theory (RST) of personality, the purpose of this study was to determine if BAS and BIS related to vocational interest and self-efficacy. Data was collected through an online survey, and a sample of 265 college students with an average age of 19.62 years old (SD = 2.81) from a large Midwestern university was obtained. Correlations between vocational interest, as measured by the Strong Interest Inventory (Donnay, Thompson, Morris, & Schaubhut, 2005), confidence, as measured by the Skills Confidence Inventory (Betz, Borgen, & Harmon, 2005), and BIS and BAS, as me

This article reports a meta-analysis of the relationships between socialnetwork site use and the Big Five personality traits (openness,conscientiousness, extraversion, agreeableness, and neuroticism) as well asthe Big Two metatraits (plasticity and stability). A random effectmeta-analysis model was used to calculate the meta-results of Big Five.Extraversion and openness were the strongest predictors of SNS activities,while conscientiousness, neuroticism, and agreeableness only correlatedwith a few of the SNS activities. A meta-analytical structural equationmodel (SEM) further demonstrated that plasticity was positively correlatedwith SNS activities, whereas stability was a negative predictor. Practicalimplications for social media industry and users are discussed.

Abstract Existing meta-analyses of Big Five personality traits and academic achievement have pooled face-to-face, blended, and online samples without testing delivery mode as a moderator. This pre-registered systematic review and meta-analysis is the first quantitative synthesis dedicated to online learning environments. Following PRISMA 2020 standards, 31 primary studies reporting Big Five (or HEXACO) personality and academic achievement in online, blended, or MOOC environments were synthesized. Ten studies (pooled N = 3,384) contributed direct Pearson correlations to the primary achievement pool, analysed with random-effects meta-analysis using Hartung-Knapp-Sidik-Jonkman adjustment on the Fisher z scale. Conscientiousness was the strongest predictor (pooled r = .167, 95% CI [.089, .243]; I² = 65.1%), followed by Agreeableness ( r = .112 [− .031, .250]), Openness ( r = .086 [− .044, .214]), Neuroticism ( r = .018), and Extraversion ( r = .002). Two pre-registered moderator effects were highly significant: Extraversion × Region (Asian samples r = − .131 vs. non-Asian r = .050; Q_between = 46.43, p < .001) and Extraversion × Outcome Type (objective r = − .038 vs. self-rated r = .117; Q_between = 17.30, p < .001). Findings provide preliminary support for the Personality-Achievement Saturation Hypothesis extended to technology-mediated learning and document novel cultural- and outcome-type-dependent shifts in the Extraversion-achievement link. GRADE confidence ranged from Moderate (Conscientiousness, Extraversion) to Low (Openness, Agreeableness, Neuroticism). Online learning modifies, but does not fundamentally transform, the established personality-achievement pattern; the most theoretically important divergences concern Extraversion and are structured by cultural context and outcome methodology.

Interest in research integrity (RI) has proliferated and gained prominence, particularly within the past decade – both in policy and academic environments. Research on RI might be considered an emerging research field, with dedicated journals and conferences. However, it is still characterized by fragmentation and is often carried out by researchers belonging to other fields (e.g. medicine, psychology, sociology, business, law, bioethics), thereby bringing varied approaches to the study of RI. The implications of this for the knowledge produced are, however, still understudied. Our study examines the place of theory in the shaping of the field of research on RI and how the choices of theoretical frameworks in given studies shape the logic of inquiry. To provide an inclusive overview of the relevant research and the theoretical variation underpinning it, we conducted systematic searches of SCOPUS, PubMed, and Web of Science (WoS) databases for English-language articles published between 2010 and 2023, based on a pre-defined set of search terms. The study finds that the theoretical landscape is highly heterogenous. It is, to some extent, dominated by grounded theory, personality psychology and institutionalism, but also engages a very broad scope of other theoretical perspectives, including social psychology, psychoanalytic theory, and narrative analysis. Through closer analysis of a group of studies that share focus on the relationship between pressure and research misconduct, this review elucidates the far-reaching implications that the choice of theory has on every aspect of an individual study and the field of research on RI overall.