Network Analysis of Self‐Efficacy and Professional Resilience in Emergency Nurses: A Multi‐Center Cross‐Sectional Study

弹性(材料科学) 网络分析 社会网络分析 护理部 医疗急救 急诊护理 心理学 梅德林 公共卫生 公共关系 业务 医学 应急响应 内容分析 定性分析 应急管理 病人护理 心理弹性 数据收集 灾害规划 紧急医疗服务
作者
C F Wang,Yinsen Peng,Lejiao Huang,Shoulin Zhu,Hanyue Zeng,Shifang Mao
出处
期刊:Journal of Advanced Nursing [Wiley]
标识
DOI:10.1111/jan.70557
摘要

OBJECTIVE: This study aimed to investigate the network structural characteristics of self-efficacy and professional resilience among emergency nurses, identify core nodes within the network, and elucidate the key interactive mechanisms between these constructs. DESIGN: Descriptive cross-sectional study. METHODS: A multi-center cross-sectional study was conducted from January to February 2025, involving 612 emergency nurses from 20 hospitals in Sichuan, China. Data were collected using a self-administered demographic questionnaire, the General Self-Efficacy Scale, and the Chinese Emergency Nurse Professional Resilience Tool. An adjacent network integrating professional resilience and self-efficacy was developed. Key covariates-including title, position, tenure in the hospital or emergency department, education, and exposure to workplace violence-were included as control variables. Network precision and stability were evaluated using the correlation stability coefficient and confidence intervals for edge weights. To further test the robustness of the network model, sensitivity analyses were performed by adding each significant covariate to the original model. The Network Comparison Test was then used to compare the covariate-adjusted and unadjusted networks, assessing differences in network structure, overall strength, and edge weights. RESULTS: The analysis identified S9 as the central node in the network. The overall network showed satisfactory stability and precision. The Network Comparison Test showed no significant differences in network structure or global strength between the adjusted and unadjusted models, indicating that the network was stable and robust to covariate adjustment. CONCLUSION: This network analysis revealed the interaction mechanisms between self-efficacy and professional resilience among emergency nurses through contemporaneous network modelling and identified S9 as the core node, suggesting that this coping strategy plays a key role in regulating psychological resources. The overall network demonstrated good stability and precision, with no statistically significant differences between the adjusted and unadjusted models according to the Network Comparison Test. These findings indicate that the network structure was robust to covariate adjustment and provide a reference for developing and optimising intervention strategies to enhance professional resilience among emergency nurses. IMPLICATIONS: For Emergency Nurses and the Management of Emergency Nursing Practice: What problem does this study address? This study addresses the gap in understanding how self-efficacy and occupational resilience interact in emergency nurses under high-stress conditions. KEY FINDINGS: A contemporaneous network analysis revealed a central node linking self-efficacy and resilience, highlighting key pathways in their mutual influence. IMPACT: The findings offer practical guidance for emergency nursing management, supporting the development of targeted strategies to strengthen nurses' resilience, enhance professional competence, and improve the quality of emergency care. REPORTING METHOD: This study is reported using the STROBE guidelines. PATIENT OR PUBLIC CONTRIBUTION: No Patient or Public Involvement: This study did not include patient or public involvement in its design, conduct, or reporting.
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