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首页> 外文期刊>Pakistan Journal of Physiology >Role of stress, emotional intelligence and resilience in well-being of staff nurses
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Role of stress, emotional intelligence and resilience in well-being of staff nurses

机译:压力,情绪智力和恢复力在工作人员护士的作用

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Background: Nurses constitute the biggest group of healthcare specialists and also have an intriguing position in healthcare system. The purpose of this study is to investigate the relationship among Stress, Emotional Intelligence, Resilience and Well-being of Staff Nurses. Methods: Data was collected from different private and government hospitals of Lahore and Islamabad within the time frame of three months (Dec 2018 to Feb 2019). Through Non-probability purposive sampling, sample of 200 was recruited. Sample size was devised through G-power analysis. Urdu translations of The Nurse Stress Index (NSI), Schutte Emotional Intelligence Scale (SEIS), Connor-Davidson, Resilience Scale (CD- RISC), BBC Well-Being Scale were used as tools to collect data. Data analysis was done with SPSS-21. Pearson Product Moment Correlation was used to find correlation between variables while Linear Regression Analysis was used to predict patterns of these conducted variables. Results: Significant positive correlation between emotional intelligence and well-being [r(200)=0.499**, p0.01] and also between resilience and well-being [r(200)=0.499**, p0.01] and a significant negative correlation between stress and well-being [r(200)= -0.253**, p0.01] was found among staff nurses. Results also indicated that the predictors (Stress, Emotional Intelligence, and Resilience) account for 34% of variance in outcome variable (Well-Being). Conclusion: The analysis of present study indicated significant correlations between variables. Study findings also revealed that demographic variables such as age, years of experience and hospital type are significantly related with the study variables.
机译:背景:护士构成了最大的医疗保健专家组,并在医疗保健系统中具有有趣的位置。本研究的目的是调查压力,情绪智力,恢复力和员工护士的福祉之间的关系。方法:在三个月的时间范围内从拉合尔和伊斯兰堡的不同私人和政府医院收集数据(2019年12月至2月)。通过非概率的目的采样,招募了200的样本。通过G功率分析设计样品大小。护士应力指数(NSI),Schutte情报秤(SEIS),Connor-Davidson,Resicience Scale(CD-RISC),BBC福祉规模的乌尔都语翻译用作收集数据的工具。使用SPSS-21完成数据分析。 Pearson产品时刻相关性用于在变量之间的相关性,而线性回归分析用于预测这些传导变量的模式。结果:情绪智力与幸福之间的显着正相关[R(200)= 0.499 **,P <0.01]以及恢复力和福祉[R(200)= 0.499 **,P <0.01]和a在员工护士中发现了应力和幸存者之间的显着的负相关[R(200)= -0.253 **,p <0.01]。结果还表明,预测器(压力,情绪智力和恢复力)占结果变量(福祉)方差的34%。结论:本研究分析表明变量与变量之间的显着相关性。研究结果还透露,人口变量如年龄,多年的经验和医院类型与研究变量有显着相关。

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