Li Yao, Dong Xue, Wang Zezhou, Yang Zhen, Zheng Xutong, Jiang Xiujie, Liu Yan, Wang Aiping
The First Affiliated Hospital of China Medical University, Shenyang, Liaoning, China.
Xuzhou Medical University, Xuzhou, Jiangsu, China.
BMC Nurs. 2025 Jul 1;24(1):795. doi: 10.1186/s12912-025-03440-y.
To investigate the current status of the ability to communicate bad news through latent profile analysis (LPA), identify potential subgroups and their population characteristics, and analyze the influencing factors of different categories.
The ability of nurses to communicate bad news is a crucial skill in clinical practice. However, heterogeneity in nurses' ability to communicate bad news and the factors influencing it have not been fully explored. Assessing the relationship with psychological resilience and work engagement is essential for understanding how these factors impact nurses' communication abilities.
This cross-sectional and multicenter study surveyed 274 Chinese nurses using a convenience sampling method. A demographic characteristics questionnaire, Communicating Bad News Scale (CBN), Connor-Davidson Resilience Scale (CD-RISC) and Utrecht work engagement scale (UWES) were used in this study, with Cronbach's alpha coefficients of 0.92, 0.91, and 0.92, respectively. Statistical analyses were performed using Mplus 8.3 and SPSS 26.0. Latent profile analysis was employed to identify nurses' ability to communicate bad news profiles using the CBN Scale. After identifying profiles via LPA, we examined their associations with psychological resilience and work engagement. Differences in sociodemographic characteristics across profiles were assessed via ANOVA, chi-square tests, and multinomial logistic regression was used to identify predictors of profile membership.
A three-profile model provided the best fit. The 3-profile were titled "Low Communicating Bad News Group" (Class 1, n = 52, 18.98%), "Medium Communicating Bad News Group" (Class 2, n = 44, 16.06%), and "High Communicating Bad News Group" (Class 3, n = 178, 64.96%). Regression analysis suggested that place of birth, psychological resilience, and work engagement were influencing factors of nurses' ability to communicate bad news (P<0.05).
Chinese nurses' ability to communicate bad news was moderate and heterogeneous, and could be categorized into three potential profiles. Nursing administrators should promptly identify and focus on the "low ability to tell bad news group" and carry out targeted interventions to improve their ability to tell bad news and enhance the quality of nursing services.
This study is the first study to explore the latent profiles of nurses' ability to communicate bad news in China. Insights from this research are useful for nursing management to identify different competence profiles of nurses, and provide targeted support and training tailored to individual needs, ultimately enhancing the quality of nursing services.
Not applicable.
通过潜在剖面分析(LPA)探讨传递坏消息能力的现状,识别潜在亚组及其人群特征,并分析不同类别影响因素。
护士传递坏消息的能力是临床实践中的一项关键技能。然而,护士传递坏消息能力的异质性及其影响因素尚未得到充分探索。评估与心理弹性和工作投入的关系对于理解这些因素如何影响护士的沟通能力至关重要。
本横断面多中心研究采用便利抽样法对274名中国护士进行调查。本研究使用了人口学特征问卷、传递坏消息量表(CBN)、康纳-戴维森弹性量表(CD-RISC)和乌得勒支工作投入量表(UWES),其克朗巴哈α系数分别为0.92、0.91和0.92。使用Mplus 8.3和SPSS 26.0进行统计分析。采用潜在剖面分析,使用CBN量表识别护士传递坏消息能力的剖面。通过LPA识别剖面后,我们检验了它们与心理弹性和工作投入的关联。通过方差分析评估不同剖面的社会人口学特征差异,使用卡方检验和多项逻辑回归来识别剖面成员的预测因素。
三剖面模型拟合最佳。这三个剖面分别为“低传递坏消息组”(第1类,n = 52,18.98%)、“中等传递坏消息组”(第2类,n = 44,16.06%)和“高传递坏消息组”(第3类,n = 178,64.96%)。回归分析表明,出生地、心理弹性和工作投入是护士传递坏消息能力的影响因素(P<0.05)。
中国护士传递坏消息的能力中等且存在异质性,可分为三种潜在剖面。护理管理者应及时识别并关注“传递坏消息能力低的群体”,开展针对性干预,以提高其传递坏消息的能力,提升护理服务质量。
本研究是国内首次探索护士传递坏消息能力潜在剖面的研究。本研究的见解有助于护理管理者识别护士的不同能力剖面,并提供符合个体需求的针对性支持和培训,最终提高护理服务质量。
不适用。