Network Analysis Of Relationships Research Articles

Network analysis of relationships between depressive symptoms and stressful life events in Chinese vocational school students

BackgroundChina's vocational high school students, approximately 13 million, confront unique stressors that may predispose them to depression. Our research investigates core and bridge depressive symptoms and their causal links with stressors in this demographic. MethodWe measured depressive symptoms and stressful life events in 4967 students aged 14–19 using the PHQ-8 and ASLEC, and analyzed the data using GGM and DAG to explore: 1) central depressive symptoms; 2) bridge symptoms/events; and 3) causal relationships. ResultsFatigue surfaced as the central depressive symptom, with guilt, sad mood, and school dislike as bridges to stressors. Guilt was pivotal in influencing other symptoms within the depression network. Fights were a primary trigger, while school dislike led to further depressive symptoms. Stressors generally led to depression, notably the study pressure to guilt pathway. A unique sad mood to heartbreak link was found. ConclusionsCore depression symptoms and bridge symptoms/events between depression and stressful life events in vocational high school students were pinpointed. The results highlight the importance of addressing interpersonal conflicts, family pressures, and emotions like fatigue and guilt to mitigate the transmission of stressful life events into depressive symptoms.

A network analysis of relationships between the work as meaning inventory (WAMI-U) and the humor styles in university students: Enhancing prevention in decent education

Rooted in the decent education as a precursor to decent work, this study investigated via network analysis the relationship between the work as meaning inventory for university students (WAMI-U) (positive meaning, meaning-making through study, greater good motivations) and the humor styles questionnaire (HSQ) (health-promoting styles: affiliative humor, self-enhancing humor; health-endangering styles: aggressive humor, self-defeating humor) in 371 Italian university students. Central nodes and bridge nodes between WAMI-U and HSQ were calculated. Positive meaning, meaning-making through study (WAMI-U), and self-enhancing humor (HSQ) had high centrality. Affiliative humor, self-enhancing humor (HSQ), and positive meaning (WAMI-U) had bridge function. The high centrality and bridge function of self-enhancing with all dimensions of WAMI-U, followed by the bridge function of affiliative humor in relation to meaning-making through study (WAMI-U) confirmed them as health-promoting styles. Negative associations between maladaptive humor styles and positive meaning (WAMI-U) confirmed their standard as health-endangering styles. Implications for research and prevention are discussed.

A network analysis of relationships between the Trait Emotional Intelligence Questionnaire Short Form (TEIQue-SF) and the Big Five personality traits in Italian workers

This study investigated the relationship between the Trait Emotional Intelligence Questionnaire Short Form (TEIQue-SF) and the ten facets of the Big Five Questionnaire (BFQ) via network analysis. The TEIQue-SF and the BFQ were administered to 751 Italian workers. Both centrality indexes (Expected Influence and Node Predictability) and bridge dimensions were calculated. Stability and accuracy were also checked to ensure the reliability of the findings. The BFQ facets of Perseverance (Consciousness) had the highest centrality while Emotion control (Emotion stability, the opposite of Neuroticism) showed high centrality. Among TEIQue-SF dimensions, Sociability followed by Emotionality and Self-Control had high centrality. TEIQue-SF Emotionality and Sociability had a bridge function. Both TEIQue-SF Emotionality and Sociability and both BFQ Perseverance and Emotion control are relevant in linking emotional intelligence and personality traits. Although further studies are needed, the network analysis represents a promising approach in providing a more detailed analysis of the relationships between dimensions of emotional intelligence and facets of personality traits in workers.

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

This study investigated the relationship between the Big Three Perfectionism Scale–Short Form (BTPS-SF) (Rigid, Self-critical, and Narcissistic perfectionism) and the ten facets of the Big Five Questionnaire (BFQ) through network analysis. The BTPS-SF and the BFQ were administered to 473 Italian workers. Both centrality indexes (Expected Influence and Node Predictability) and bridge dimensions were calculated. Stability and accuracy were also checked to ensure the trustworthiness and reliability of the findings. The network analysis showed that BTPS-SF Rigid Perfectionism had the highest centrality and a bridge function, whereas BFQ Dominance had a bridge function. Findings suggested that BTPS-SF Rigid Perfectionism and BFQ Dominance are relevant in linking perfectionism and personality traits. Although further studies are needed, the network approach can provide a promising realm for understanding relationships between perfectionism and personality traits.

Working cooperatively in an age of deregulation

This paper outlines the first part of a longitudinal study exploring strategic alliances as central mechanisms of inter‐firm cooperation in the Australian telecommunications sector. It reports on the collaboration practices of the three carriers – Telecom, Optus and Vodafone – and their first‐tier “partners”. The Australian telecommunications industry is a useful site for theory testing and development because of its degree of business concentration, the strategic relationships and networks involved and the role of government in encouraging alliances and networks, especially since the move away from a single government‐owned monopoly‐carrier environment. The recent proliferation of interorganisational alliances means we need new approaches to understanding and a move away from simple assumptions about complex organizational structures and processes. Neither is the current superficial rhetoric promoting such arrangements as the answer to industry ills adequate. Conseqently, the present study aims to enhance more complex understanding of how such structural arrangements actually work – how they are formed, organized and managed over time. The study methodology centres on analysis of research and in‐depth interviews with key industry and government executives. Proposed extensions of the present work involve a detailed communications industry survey and network analysis of relationships, with a special focus on relationships growing in the convergence of the telecommunications, entertainment, computing and media industries. When quotations from study participants are used, sources are generally not acknowledged in an endeavour to keep as much anonymity as possible.