工作投入
比例(比率)
医学
工作(物理)
构造(python库)
逻辑回归
多项式logistic回归
护理部
应用心理学
心理学
量子力学
机械工程
机器学习
物理
内科学
工程类
程序设计语言
计算机科学
作者
Xiaoming Xiong,Xuan Huang,Chongqing Shi,Zheng Xu,Xiang Rao
出处
期刊:BMJ Open
[BMJ]
日期:2025-03-01
卷期号:15 (3): e087497-e087497
标识
DOI:10.1136/bmjopen-2024-087497
摘要
Objective To identify different work engagement profiles among new nurses in China and explore demographic and personal factors that predict different work engagement profiles. Design A cross-sectional study. Methods From 1 April to 30 June 2022, a cross-sectional survey was conducted in 11 tertiary hospitals across five provinces in China. Using a convenience sampling method, 662 new nurses were recruited to participate. Data were collected using standardised instruments, including the Work Engagement Scale, the Difficulties in Emotion Regulation Scale and the Job Crafting Scale. Latent profile analysis was employed to identify latent profiles of work engagement among new nurses, and multinomial logistic regression analysis was used to examine predictors of different work engagement profiles. Results This study identified three potential profiles of work engagement among new nurses, namely the ‘low work engagement group’ (15%), the ‘moderate work engagement group’ (62%) and the ‘high work engagement group’ (23%). Independent nursing work, emotion regulation training, difficulties in emotion regulation and job crafting were predictors of different work engagement profiles. Conclusions Nursing supervisors are advised to pay more attention to and help new nurses who work independently, strengthen relevant training on emotion regulation strategies for new nurses and construct intervention strategies based on job crafting, so as to improve the work engagement level of new nurses.
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