Malekiha Marzieyh, Hosseinzadeh Leila, Zaremohzzabieh Zeinab
Department of Counseling, Hazrat-e Masoumeh University, Qom, Iran.
Islamic Azad University Khorasghan Branch, Isfahan, Iran.
BMC Nurs. 2025 Jul 18;24(1):946. doi: 10.1186/s12912-025-03604-w.
Compassion is a core element of helping professions, particularly nursing; however, prolonged exposure to emotional demands can lead to compassion fatigue, negatively impacting performance and care quality. This study aimed to predict the role of personality traits and socio-emotional support in compassion fatigue among nurses at Al-Zahra Hospital in Isfahan, Iran.
A cross-sectional study was used to examine the predictors of compassion fatigue among nurses. The study sample consisted of 270 registered nurses employed at three public hospitals in Isfahan, Iran. A stratified sampling method was employed to ensure proportional representation from various hospital wards, including emergency, intensive care, and general units. Data were collected using a self-administered questionnaire that included demographics, the ProQOL for compassion fatigue, the NEO Personality Inventory, and the Socio-Emotional Support Scale (SESS). All statistical analyses were conducted using IBM SPSS Statistics for Windows, Version 26.0. Stepwise multiple linear regression identified predictors of compassion fatigue, and hierarchical regression tested interaction effects.
A stepwise multiple regression analysis revealed that extraversion (β = 0.531, p < .001), openness to experience (β = - 0.552, p < .001), neuroticism (β = 0.405, p < .001), and socio-emotional support (β = - 0.145, p = .011) significantly predicted compassion fatigue. Together, these variables explained 41.6% of the variance (R² = .416, F(4, 265) = 47.26, p < .001). A hierarchical regression further showed significant interaction effects: Neuroticism × Socio-emotional Support (β = 0.182, p = .004) and Openness × Socio-emotional Support (β = - 0.156, p = .015), increasing the total variance explained to 44.2% (R² = .442, F(6, 263) = 34.72, p < .001). These findings suggest that personality traits and socio-emotional support, including their interactions, play a significant role in predicting compassion fatigue among nurses.
A significant portion of compassion fatigue among nurses was predicted by personality traits and socio-emotional support. These findings highlight the need for targeted interventions, such as psychological screening and support programs, tailored to individual risk profiles. Future qualitative research is recommended to explore nurses' experiences with compassion fatigue in clinical settings.
同情心是助人职业的核心要素，尤其是护理工作；然而，长期暴露于情感需求中会导致同情疲劳，对工作表现和护理质量产生负面影响。本研究旨在预测人格特质和社会情感支持在伊朗伊斯法罕扎赫拉医院护士同情疲劳中的作用。
采用横断面研究来检验护士同情疲劳的预测因素。研究样本包括伊朗伊斯法罕三家公立医院的270名注册护士。采用分层抽样方法以确保各医院科室（包括急诊科、重症监护室和普通科室）的比例代表性。使用自填式问卷收集数据，问卷包括人口统计学信息、同情疲劳的职业生活质量量表、大五人格量表和社会情感支持量表（SESS）。所有统计分析均使用IBM SPSS Statistics for Windows 26.0版进行。逐步多元线性回归确定同情疲劳的预测因素，层次回归检验交互效应。
逐步多元回归分析显示，外向性（β = 0.531，p <.001）、开放性（β = -0.552，p <.001）、神经质（β = 0.405，p <.001）和社会情感支持（β = -0.145，p = 0.011）显著预测了同情疲劳。这些变量共同解释了41.6%的方差（R² = 0.416，F(4, 265) = 47.26，p <.001）。层次回归进一步显示了显著的交互效应：神经质×社会情感支持（β = 0.182，p = 0.004）和开放性×社会情感支持（β = -0.156，p = 0.015），使解释的总方差增加到44.2%（R² = 0.442，F(6, 263) = 34.72，p <.001）。这些发现表明，人格特质和社会情感支持，包括它们的相互作用，在预测护士的同情疲劳中起着重要作用。
护士同情疲劳的很大一部分可由人格特质和社会情感支持预测。这些发现凸显了针对个体风险特征进行有针对性干预的必要性，如心理筛查和支持项目。建议未来进行定性研究，以探索护士在临床环境中同情疲劳的经历。
