Network analysis maps how stress, belonging and failure mindset connect in nursing students

Nursing students moving from classroom learning into clinical practice face a tangle of psychological pressures, and a new cross-sectional study has tried to map exactly how those pressures interconnect. Using a network analysis approach, researchers examined role stress, emotional labor, sense of belonging in nursing school, and failure mindset among 308 nursing students undertaking clinical practice at a college in Wuzhou, Guangxi, China. The survey was conducted between November and December 2025, and the results suggest that a small number of specific dimensions sit at the center of this interconnected system.

The study, published in BMC Nursing, was motivated by a limitation in earlier work. Previous research on student adjustment during clinical training has largely used variable-centered approaches, which examine each factor in isolation. That makes it difficult to identify which psychological and educational targets matter most within a system where everything is connected to everything else. Network analysis addresses this by modeling the direct associations between individual dimensions, revealing which nodes are most strongly linked and which bridge different domains.

The researchers then estimated a regularized partial correlation network using a Gaussian graphical model with the EBICglasso procedure. Expected influence was used to identify the most central nodes in the network, while bridge expected influence was used to find nodes that connect otherwise separate domains. Network accuracy and centrality stability were evaluated with bootstrap procedures.

The results point to clinical practice belonging, role overload, and role conflict as among the more highly connected nodes in the network. Role overload stood out in particular: it showed a high level of both strength and predictability, meaning it was strongly connected to other nodes and largely explained by its neighbors. In practical terms, feeling overloaded in one’s role appears tightly woven into the wider fabric of student experience during clinical placement.

The strongest single edge in the network was between role conflict and role overload, an intuitive but now empirically documented pairing. It was followed by the edges between clinical practice belonging and clinical teaching, between clinical teaching and school teachers, and between surface acting and deep acting. These connections suggest that relationships with teachers, both clinical and school-based, travel together with students’ sense of belonging, while the two emotional labor strategies form their own closely linked pair.

When the researchers looked for bridge nodes, positive failure mindset showed the highest point estimate for bridge expected influence, followed by role overload and surface acting. This means these dimensions may serve as exploratory candidate bridges connecting different domains of the network, potentially linking how students interpret failure to how they manage role demands and regulate emotional display. The centrality estimates showed good stability, with correlation stability coefficients of 0.672 for both strength and expected influence, indicating the central node rankings were unlikely to be statistical artifacts.

The authors are careful about what these findings do and do not show. Because the study was cross-sectional and exploratory, the identified dimensions should be regarded as candidate hypotheses for longitudinal or intervention research rather than as established causal factors. A single snapshot cannot establish whether role overload drives poor belonging, whether belonging buffers overload, or whether both arise from some other source. The sample also came from one college in one Chinese city, so generalization to other settings remains an open question.

Even with those limits, the study offers a concrete starting point for support programs. The findings suggest that educational and psychological support for nursing students during clinical practice may consider strategies aimed at reducing excessive role demands, strengthening students’ belonging in clinical practice, promoting adaptive interpretations of failure, and reducing reliance on surface acting. By treating these as candidate targets rather than proven levers, the network approach gives future longitudinal and intervention studies a prioritized shortlist of where to look first.

Subject of Research: Network analysis of role stress, emotional labor, sense of belonging and failure mindset among nursing students during clinical practice

Article Title: Role stress, emotional labor, sense of belonging in nursing school, and failure mindset among nursing students during clinical practice: a cross-sectional network analysis

Article References: Liang, Y., Liang, Y., Zhou, X., & Bi, J. (2026). Role stress, emotional labor, sense of belonging in nursing school, and failure mindset among nursing students during clinical practice: a cross-sectional network analysis. BMC Nursing. https://doi.org/10.1186/s12912-026-05582-z

Image Credits: AI Generated

DOI: 10.1186/s12912-026-05582-z

Keywords: nursing students, clinical practice, role stress, emotional labor, sense of belonging, failure mindset, network analysis, cross-sectional study, role overload, surface acting, China, nursing education