Towards an explanatory personality psychology: Integrating personality structure, personality process, and personality development

My Perceptions are not your Perceptions: The Mediating Role of Cognitive Appraisal on the Association between the Big Five Personality Traits and Emotional Reactivity

Personality, the enduring pattern of affect, behaviors, cognitions, and desires, strongly predicts important outcomes, such as mental and physical health, and specific emotional reactions. However, the reasons behind these associations are still unclear, and explanatory processes are now being searched for. Appraisal theories of emotion, particularly the Component Process Model of emotion, can help to address this gap. In this model, an appraisal process, a situational cognitive evaluation, influences emotion unfolding by activating concomitant experiential, expressive, motivational and physiological responses. While evidence on the personality-appraisal relationship exists, specific knowledge about the potential mediatory role of appraisal in this relationship is very sparse, although it could explain how personality might shape emotional reactions. In a survey, we evaluated the personality of 500 participants (MAge = 22.41; Females = 83.2%) and confronted them with two emotional scenarios of different valences. Leveraging exploratory mediation analysis (EMA), we found that, in the Negative Scenario, the appraisals of negative consequences, powerlessness, and future consequences adjustment emerged as the most influential mediators, being differentially implicated in the relationship between Neuroticism, on the one hand, and the Feeling and Autonomic Arousal components, on the other hand. Mediation pathways in the Positive Scenario were more diverse, with the appraisal of powerlessness again emerging as a relevant mediator in the relationship between traits and emotional outcomes. This study highlights appraisal as a fundamental explanatory mechanism linking individual differences to emotional responses. Appraisal could be thus leveraged in interventions to allow certain personality to take the path of specific, healthier affective outcomes.

Unpacking interplays between competitiveness, cooperativeness, and social comparison orientation: A network psychometric approach and replication

Emerging evidence highlights the role of social comparison in competition and cooperation, yet the dynamics among competitiveness, cooperativeness, and social comparison orientation (SCO) remain underexplored. In the present study, we sought to unravel these complex interplays employing graphical Gaussian models (GGMs) and characterize the network structures utilizing cross-sectional data derived from 1073 Chinese participants. A pre-registered independent sample (n = 1348) served to examine the replicability and robustness of our initial findings. Moreover, we explored the Bayesian networks (i.e., directed acyclic graphs) to delve into their probabilistic directed dependencies. Our analysis identified an interpersonal co-opetition network where SCO bridges competitiveness and cooperativeness, emphasizing the key influence of the desire to surpass others. We also found a significant gender effect on the levels of these orientations but not on the network patterns. Additionally, the replication sample offered validation for the resultant network structure and its key nodes. In sum, these findings provide a new insight into the symbiotic relationship between competitiveness and cooperativeness within the framework of social comparison, offering significant theoretical and practical implications.

The Alternative Model of Personality Disorders: Assessment, Convergent and Discriminant Validity, and a Look to the Future

The Alternative Model of Personality Disorders (AMPD) is a dimensional, empirically based diagnostic system developed to overcome the serious limitations of traditional categories. We review the mounting evidence on its convergent and discriminant validity, with an incursion into the less-studied ICD-11 system. In the literature, the AMPD's Pathological Trait Model (Criterion B) shows excellent convergence with normal personality traits, and it could be useful as an organizing framework for mental disorders. In contrast, Personality Functioning (Criterion A) cannot be distinguished from personality traits, lacks both discriminant and incremental validity, and has a shaky theoretical background. We offer some suggestions with a view to the future. These include removing Criterion A, using the real-life consequences of traits as indicators of severity, delving into the dynamic mechanisms underlying traits, and furthering the integration of currently disengaged psychological paradigms that can shape a sounder clinical science.

The whole is more than the sum of its parts: A qualitative investigation of body-dissatisfied college women's experiences of relational body image

Research on relational body image suggests that women's body image changes across their important relationships, with women most at risk for maladaptive body image reporting the most extreme changes. To enrich our understanding of relational body image beyond that offered by prior psychologically-based quantitative research, the present study integrated critical-feminist approaches. Eighteen female-identified university students participated in a one-on-one semi-structured interview. Each participant first completed ratings of her body image across seven important relationships, which the interviewer used to create a graph depicting her relational body image. The interviewer shared the graph with the participant to prompt reflection on her subjective experiences of relational body image and asked her a series of questions. Reflexive thematic analysis, informed by a critical-realist framework, was used to identify themes. One overarching theme, "The Whole Is More than The Sum of Its Parts," demonstrated how relational body image may be understood as a unique configuration of interconnected factors within a specific relationship. Three subthemes then highlighted how interpersonal, idiographic, and systemic factors come together to influence subjective experiences of relational body image. The present results suggest that personalized treatment targets within specific relationships may be a worthwhile focus for future body image interventions.

Negative internal working models as mechanisms that link mothers' and fathers' personality with their parenting: A short-term longitudinal study

OBJECTIVE

Research on associations between parents' personality and parenting has a long history, but mechanisms that explain them remain unsettled. We examined parents' explicit and implicit negative internal working models (IWMs) of the child, assessed at toddler age, as linking parental personality and parenting.

METHOD

Mothers and fathers from 200 community families provided personality self-reports (Neuroticism, Agreeableness, Empathy, and Anger/Hostility) when their children were infants. When children were toddlers, the explicit negative IWMs included self-reported low-mentalizing reflective functioning and resentment regarding the child. The implicit negative IWMs were coded as negative relational schemas from parental interviews. Parental positive affect, responsiveness, and power-assertive control were observed in lengthy interactions. Measures were parallel for mother- and father-child dyads.

RESULTS

Mothers' implicit IWMs linked the association between low Empathy and more power-assertive control. Fathers' explicit IWMs linked the associations between high Neuroticism and low Agreeableness and lower responsiveness. Additionally, fathers' Agreeableness and Empathy directly predicted their parenting. Two paths (Agreeableness → implicit IWMs, and explicit IWMs → responsiveness) significantly differed between mothers and fathers.

CONCLUSIONS

IWMs may link parental personality with parenting. The findings integrate and inform several bodies of literature in personality, social cognition, and developmental psychology.

The Psychosocial Factors Affecting Chinese Outbound Exchange and Mobility Students' Academic Performance During COVID-19

COVID-19 has affected every aspect of our life, including economic, social, and academic. Exchange and mobility students face more difficulties overseas, and Chinese students are no exception. However, e-learning has been introduced by institutions in many countries. The present study examines the psychosocial factors affecting the academic performance of Chinese outbound exchange and mobility students during the COVID-19 pandemic. The study surveys about 186 Chinese outbound exchange and mobility students. The present study performs the quantitative data analysis using Partial Least Square Structural Equation Modeling (PLS-SEM) through the Smart PLS software version 3. By confirming the measurement model and structural model assessments, the study finds that personality, social support, and language fluency are psychosocial factors that significantly influence the exchange and mobility students' academic performance. This study contributes by establishing relationships among psychosocial factors, language fluency and academic performance. Besides, practitioners can be benefitted by understanding students' psychosocial factors and its relation to academic performance during COVID-19 pandemic.

EEG-Based Personality Prediction Using Fast Fourier Transform and DeepLSTM Model

In this paper, a deep long short term memory (DeepLSTM) network to classify personality traits using the electroencephalogram (EEG) signals is implemented. For this research, the Myers-Briggs Type Indicator (MBTI) model for predicting personality is used. There are four groups in MBTI, and each group consists of two traits versus each other; i.e., out of these two traits, every individual will have one personality trait in them. We have collected EEG data using a single NeuroSky MindWave Mobile 2 dry electrode unit. For data collection, 40 Hindi and English video clips were included in a standard database. All clips provoke various emotions, and data collection is focused on these emotions, as the clips include targeted, inductive scenes of personality. Fifty participants engaged in this research and willingly agreed to provide brain signals. We compared the performance of our deep learning DeepLSTM model with other state-of-the-art-based machine learning classifiers such as artificial neural network (ANN), K-nearest neighbors (KNN), LibSVM, and hybrid genetic programming (HGP). The analysis shows that, for the 10-fold partitioning method, the DeepLSTM model surpasses the other state-of-the-art models and offers a maximum classification accuracy of 96.94%. The proposed DeepLSTM model was also applied to the publicly available ASCERTAIN EEG dataset and showed an improvement over the state-of-the-art methods.