Perfectionism: A network analysis of relationships between the Big Three Perfectionism dimensions and the Big Five Personality traits

Understanding the relationships among adolescents' internet dependence, reward, cognitive control processing, and learning burnout: a network perspective in China

Alterations in the reward and cognitive control systems are commonly observed among adolescents with internet dependence (ID), and this impairment is often accompanied by social dysfunctions, such as academic burnout. However, the intercorrelations among ID, reward, cognitive control processing, and learning burnout remain unclear. We recruited 1074 Chinese adolescents to investigate the complex interrelationships among these variables using network analysis. The resulting network revealed patterns that connected ID to the behavioral inhibition/activation system (BIS/BAS), self-control, and learning burnout; these results exhibited reasonable stability and test-retest consistency. Throughout the network, the node of BAS-drive was the critical influencing factor, and the node of self-control was the protection factor. In addition, several symptoms of learning burnout and ID were positively associated with sensitivity to punishment. As revealed by the network comparison test, the network constructed among internet dependent (ID) group differed from the network constructed among internet nondependent (IND) group not only in the edges between BIS and learning burnout but also in terms of the edges associated with learning burnout. In conclusion, this study provides insights into the complex mechanisms underlying ID among adolescents from the perspective of the network relationships between core influencing factors and negative consequences. It validates the dual-system model of risky behavior among adolescents and offers a foundation for early warning and interventions for ID in this context.

Maintenance in relationships, satisfaction, jealousy, and violence in young couples: a network analysis

BACKGROUND

The study explores the associations among Relationship Maintenance, Satisfaction, Jealousy, and Violence in young Peruvian couples, particularly in a post-pandemic context, using a network analysis.

METHODS

Eight hundred thirty-two participants aged 18-30 (M = 20.94, SD = 2.29), with 645 females (77.50%) and 187 males (22.50%), were involved. The study aimed to discern relationships among network nodes, emphasizing the link between Relationship Maintenance dimensions and Jealousy and Violence. The research also sought the central node in the network and examined gender-specific node connections, using the SMOTE algorithm for gender data balance.

RESULTS

Findings revealed a direct connection between Complementarity and Jealousy, implying intense shared interests can lead to unhealthy dependence. An inverse relationship was seen between Companionship and Violence. Satisfaction was pivotal, showcasing its importance in romantic relationship success. Additionally, the study shows men prioritize Companionship and Sharing, possibly due to cultural norms, while women focus on the Companionship-Complementarity bond, indicating mutual support.

CONCLUSIONS

The research emphasizes the critical role of maintenance variables in determining Satisfaction, Jealousy, and Violence in relationships. The pandemic's influence on romantic dynamics is evident, emphasizing the importance of Satisfaction. Future studies should focus on gender equity and further explore these relationships.

The Symptom Network Structure of Teachers' Burnout and Its Connection to Psychological Capital

Background

Teacher burnout is characterized by emotional and physical exhaustion resulting from excessive work-related stress. Previous research based on traditional latent variable theory has revealed a significant negative relationship between TB and psychological capital (PsyCap). This study explored the complex symptoms of TB and the contact points of PsyCap in reducing TB using psychometric network analysis.

Methods

A total of 3991 teachers completed the burnout subscale of the Professional Quality of Life and Psychological Capital Scale.

Results

The results showed that: (a) In the TB network, the core symptoms displayed by teachers due to burnout are difficulty feeling "I am a very caring person", "I am happy", and "I am the person I always wanted to be"; (b) The TB-PsyCap network was closely connected, and the symptoms affected each other. PsyCap affected the TB network through "I feel optimistic and happy almost every day" and "I often feel that there is a future as a teacher"; (c) PsyCap's bridge symptoms had a negative impact on TB, and PsyCap may reduce TB primarily through optimistic, hopeful dimensions.

Conclusion and Implications

Psychometric network analysis helps us understand the complex symptoms of TB and the contact points of PsyCap in reducing TB. This study offers valuable insights into the prevention of, and intervention in, burnout within the teaching community.

Human capital sustainability leadership: From personality traits to positive relational management

Introduction

Constructing positive and supportive relationships is fundamental for healthy workers and healthy organizations and to cope with the current challenging work scenario. Organizations need to acknowledge the relevance of the relationships for workers and organizational well-being and adopt managing practices that enhance healthy relationships for sustainability and sustainable development.

Methods

The current research sought to investigate the associations between positive relational management (PRM) and human capital sustainability leadership (HCSL), taking into account personality traits. The big five questionnaire (BFQ), the PRM Scale (PRMS), and the HCSL Scale (HCSLS) were administered to 191 Italian workers.

Results

Findings displayed that PRM was able to add incremental variance over personality traits referring to HCSL.

Discussion

In terms of strength-based prevention perspectives for healthy organizations, PRM may be a favorable construct linked to HCSL.

Relationships between Humor Styles and the Big Five Personality Traits in Workers: A Network Analysis

In this study, we investigated the relationship between the four humor styles (Affiliative, Self-enhancing, Aggressive, and Self-defeating) assessed via the Humor Styles Questionnaire (HSQ) and the ten facets of the Big Five Questionnaire (BFQ) through network analysis. Four hundred and sixty-two Italian workers (61.3% women; Mage = 48.59; SD = 10.75) participated in the study and filled out the HSQ and the BFQ. Both centrality indexes (Expected Influence [EI]) and bridge nodes were calculated. In addition, the stability and accuracy of the network were checked. The network analysis revealed that HSQ Self-enhancing (EI = 0.63) showed the highest centrality among the HSQ styles, whereas BFQ Emotion Control (EI = 1.10) showed the highest centrality among BFQ facets; it also revealed that they were positively linked. Furthermore, HSQ Self-defeating emerged as the second-most-central humor style, negatively associated with BFQ Emotion Control. Concerning Bridge dimensions, four nodes were identified: HSQ Aggressive Humor, BFQ Emotion Control, BFQ Dynamism, and BFQ Dominance, with positive links between humor and personality except for Aggressive humor and Emotion Control, which showed negative links. On the basis of these results, the high centrality of HSQ Self-enhancing indicates the possibility of using this node as a starting point to foster positive and adaptive humor styles. The centrality of HSQ Self-defeating suggests that strength-based interventions could be focused to increase adaptive humor styles and to decrease them in order to enhance health-promoting humor styles. Furthermore, the bridge node of the HSQ Aggressive humor style with specific personality facets shows its possible use in intervention to both resize and to adaptively improve relationships between humor and personality.

The Gratitude Resentment and Appreciation Test-Revised Short (GRAT-RS): A Multidimensional Item Response Theory Analysis in Italian Workers

Gratitude is a promising resource from a healthy organizational perspective. It is related to many positive outcomes at work. The Gratitude Resentment and Appreciation Test-Revised Short (GRAT-RS) is the most widely used self-report questionnaire to detect gratitude. The present study examined GRAT-RS (the Italian version) by implementing multidimensional item response theory (MIRT) analyses to explore its psychometric properties. The participants were 537 Italian workers. Confirmatory factor analyses (CFA) of the GRAT-RS and MIRT analyses using the Grade Response Model were run. The MIRT discrimination and MIRT difficulty parameters were calculated. A test information function (TIF) and measure of reliability associated with (TIF) scores were also implemented. CFA highlighted that a bifactor model showed the best fit. Hence, MIRT analyses were carried out by implementing a bifactor model. The MIRT bifactor structure showed a good data fit with discrimination parameters ranging from good to excellent and adequate reliability. The good psychometric properties of GRAT-RS were confirmed, highlighting the questionnaire as a reliable tool to measure gratitude in Italian workers.

The Sustainable Development Goals Psychological Inventory: A Network Analysis in Italian University Students

The Sustainable Development Goals Psychological Inventory (SDGPI) is a recently developed self-report questionnaire that assesses interest, motivation, and self-efficacy associated with each of the 17 Sustainable Development Goals (SDGs) advanced by the United Nations. This study aims to investigate, via network analysis, (a) the relationships between interest, motivation, and self-efficacy for each SDG and (b) the most central SDGs. To this end, 417 Italian university students (73.9% females and 26.1% males; mean age: 22.20; DS = 3.02) were assessed through the SDGPI, and two network structures were estimated. The first network structure investigates links (edges) between interest, motivation, and self-efficacy in relation to each specific SDG. The second network structure investigates most central SDGs as the sum of interest, motivation, and self-efficacy for each specific SDG. Regarding results, the first network structure showed that five SDGs had strong and statistically significant edges between interest, motivation, and self-efficacy; seven SDGs had strong and statistically significant edges between interest and motivation but not self-efficacy; five SDGs had no statistically significant edges linking the other dimensions. The second network structure revealed that SDG 2 (Zero Hunger) and SDG 7 (Affordable and clean energy) were the most central nodes. Implications for research, tailor-made interventions, and prevention were discussed.