ArticleFrontiers in public health2026
Network analysis of psychological and behavioral variables in firefighters: identification of central nodes and bridge variables.
Article in Frontiers in public health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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1 citing paper in PubMed.
- Identifying profile-specific candidate targets for miner safety: a latent class and network analysis of psychological resources.Frontiers in psychology · 2026Article
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5 authors.
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Abstract
Objective: This study employed network analysis to systematically explore the complex associative structure among 14 psychological and behavioral variables in firefighters, including burnout, job stress, work-family conflict, social support, sleepiness, self-efficacy, and physical activity. The aim was to identify central nodes and cross-system bridge variables to inform targeted psychological interventions. Methods: A sample of 637 Chinese firefighters was recruited. Fourteen psychological and behavioral variables were included to construct a psychological network model using the EBICglasso regularized partial correlation method. Strength centrality, closeness centrality, betweenness centrality, and expected influence were calculated to identify central nodes. Bridge centrality indices were computed to identify cross-system bridge variables. Network stability was assessed using non-parametric bootstrap and case-dropping bootstrap procedures. Results: The strongest edge weight in the network was between emotional exhaustion and depersonalization (weight = 0.676), followed by work interference with family and family interference with work (weight = 0.633), interpersonal stress and role stress (weight = 0.535), and significant-other support and friend support (weight = 0.512). The node with the highest strength centrality was emotional exhaustion (1.29), followed by depersonalization (0.85) and interpersonal stress (0.70). Bridge centrality analysis revealed that reduced personal accomplishment (bridge strength = 0.581), family interference with work (0.558), and self-efficacy (0.525) exhibited high bridge strength, while sleepiness (bridge expected influence = 0.477) served as the key bridge variable connecting other psychological systems. Robustness checks indicated that the correlation stability (CS) coefficients for strength centrality and expected influence were both 0.75 (exceeding the 0.50 benchmark), confirming the stability and reliability of the network structure. Conclusion: Emotional exhaustion represents the core feature in the psychological problem network of firefighters. Sleepiness and self-efficacy serve as key bridge variables connecting different psychological systems. These findings suggest that emotional exhaustion, self-efficacy, and sleepiness may serve as empirically prioritized candidates for future longitudinal studies and targeted intervention research aimed at promoting firefighter mental health.
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