Li Bing, Huang Yanling, Liu Qian, Xiao Peiduo, Li Lichang, Zeng Kun
Guangdong Pharmaceutical University, Guangzhou, Guangdong, China.
Dongguan Eighth People's Hospital, Dongguan, Guangdong, China.
BMJ Open. 2025 Sep 2;15(9):e101039. doi: 10.1136/bmjopen-2025-101039.
This study sought to evaluate the prevalence of empathy for pain among nurses in Chinese hospitals through latent profile analysis, identify latent subgroups and their demographic characteristics and examine the relationship between different subgroups and coping styles.
A multicentre cross-sectional study.
The study was conducted in 43 hospitals across Guangdong Province, China, comprising 36 general medical hospitals and 7 specialty hospitals.
This study recruited 1656 registered nurses with over 1 year of clinical experience from 43 hospitals in Guangdong Province, China, using a convenience sampling method between June and September 2023. A total of 1601 valid questionnaires were returned, with a response rate of 96.68%.
Data were collected through online questionnaires using the General Information Questionnaire, the Chinese Version of the Empathy for Pain Scale and the Simplified Coping Style Questionnaire. Latent profile analysis was applied to assess the characteristics of nurses' empathy for pain, while logistic regression analysis was employed to identify factors influencing the different empathy for pain profiles.
The mean empathy for pain score among the 1601 clinical nurses was 2.92±0.79. Nurses' empathy for pain was categorised into three latent profiles: low empathy sensitivity (33.9%), balanced response (48%) and empathy contradiction (18.1%). Univariate analysis demonstrated significant variations in the distribution of nurses across different profiles concerning age, marital status, childbearing status, perceived pain tolerance, job satisfaction, participation in pain-related knowledge training, designation as a pain resource nurse and coping styles scores. Logistic regression analysis identified perceived pain tolerance, job satisfaction and coping styles as significant determinants of nurses' latent empathy for pain profiles (p<0.05).
Nurses' empathy for pain characteristics exhibits heterogeneity and can be categorised into three latent profiles. Nursing managers should implement targeted interventions tailored to each profile, focusing on the key determinants such as perceived pain tolerance, job satisfaction and coping styles. These interventions can enhance nurses' empathy for pain, promote the adoption of positive coping styles and ultimately improve clinical pain management and overall nursing care quality.
本研究旨在通过潜在类别分析评估中国医院护士对疼痛的共情患病率,识别潜在亚组及其人口统计学特征,并检验不同亚组与应对方式之间的关系。
多中心横断面研究。
本研究在中国广东省的43家医院进行,包括36家综合医院和7家专科医院。
本研究于2023年6月至9月采用便利抽样法,从中国广东省43家医院招募了1656名具有1年以上临床经验的注册护士。共回收有效问卷1601份,有效回收率为96.68%。
通过在线问卷收集数据,使用一般信息问卷、中文版疼痛共情量表和简易应对方式问卷。应用潜在类别分析评估护士对疼痛的共情特征,同时采用逻辑回归分析确定影响不同疼痛共情特征的因素。
1601名临床护士的疼痛共情平均得分为2.92±0.79。护士对疼痛的共情分为三种潜在类别:低共情敏感性(33.9%)、平衡反应(48%)和共情矛盾(18.1%)。单因素分析表明,不同类别护士在年龄、婚姻状况、生育状况、疼痛耐受感知、工作满意度、参与疼痛相关知识培训、担任疼痛资源护士以及应对方式得分方面的分布存在显著差异。逻辑回归分析确定疼痛耐受感知、工作满意度和应对方式是护士潜在疼痛共情特征的重要决定因素(p<0.05)。
护士对疼痛的共情特征存在异质性,可分为三种潜在类别。护理管理者应针对每种类别实施有针对性的干预措施,重点关注疼痛耐受感知、工作满意度和应对方式等关键决定因素。这些干预措施可以增强护士对疼痛的共情,促进积极应对方式的采用,最终改善临床疼痛管理和整体护理质量。