Evidence map›Paper›PMID 42487806›Full record

ArticleFrontiers in public health2026

The relationship between role clarity and compulsory citizenship behavior among junior nurses: evidence from network analysis and simulation-based network modeling.

Tingyao Nie, WeiKe Zeng, Hang Liu, Lu Lin, Miao Chen

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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. Not yet cited in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Tingyao NieDepartment of Geriatrics, The First Hospital of Hunan University of Chinese Medicine, Hunan, China.
WeiKe ZengContemporary Nurse Co., Ltd., Changsha, Hunan, China.
Hang LiuNursing Teaching and Research Office, The First Affiliated Hospital of Zhengzhou University, Henan, China.
Lu LinXiangya School of Nursing, Central South University, Changsha, Hunan, China.
Miao ChenDepartment of Thoracic Surgery, The First Hospital of Hunan University of Chinese Medicine, Hunan, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Compulsory Citizenship Behavior (CCB) among junior nurses may undermine occupational wellbeing and workforce stability. Role clarity has been considered an important organizational resource, yet its item-level associations with CCB remain insufficiently understood. In addition, workplace violence (WPV) may shape the way in which role-related perceptions are associated with compulsory extra-role behaviors. This study aimed to explore the network associations between role clarity and CCB among junior nurses and to compare network structures between nurses with and without WPV exposure. Methods: A cross-sectional survey was conducted among junior nurses from hospitals in three provinces of China. Participants completed self-report questionnaires assessing role clarity, CCB, and WPV exposure. Network analysis was used to estimate item-level associations between role clarity and CCB. Bridge centrality indices were calculated to identify items that showed stronger statistical connections across constructs. Network comparison analyses were conducted between nurses with and without WPV exposure. Simulation-based prediction analysis was further performed to explore how changes in selected nodes might be statistically associated with changes in the overall network. Results: The estimated networks showed meaningful item-level associations between role clarity and CCB. Several items demonstrated relatively high expected influence or bridge expected influence, suggesting that they may occupy important positions in the statistical network. Network structures differed between nurses with and without WPV exposure, indicating that WPV exposure may be associated with different patterns of connections between role clarity and CCB. Simulation-based prediction suggested that changes in selected nodes may correspond to changes in predicted CCB levels within the estimated network model. Conclusion: This study provides preliminary evidence on the network associations between role clarity and CCB among junior nurses. The findings suggest that specific role-related and CCB-related items may serve as potential candidates for future organizational assessment or intervention development. However, because this study used a cross-sectional self-report design and simulation-based prediction rather than experimental intervention, causal interpretations should be avoided. Future longitudinal and intervention studies are needed to verify the temporal and causal mechanisms underlying these associations.

Indexed as

Nursing Staff, HospitalAdultChinaCross-Sectional StudiesFemaleHumansMaleSurveys and QuestionnairesWorkplace ViolenceCompulsory Citizenship Behaviorcomputer-simulated network interventionjunior nursesnetwork analysisrole clarityworkplace violence

Identifiers

PMID42487806
PMCPMC13388927

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.