Abid Mueen, Riaz Maryam, Bano Zaqia, Parveen Tahira, Umar Fayyaz Muhammad, Sadia Qureshi Halima
Department of Psychology, University of Gujrat, Gujrat, Pakistan.
Department of Psychology, National University of Medical Sciences Rawalpindi, Rawalpindi, Pakistan.
Front Psychol. 2021 Oct 1;12:734623. doi: 10.3389/fpsyg.2021.734623. eCollection 2021.
To determine the predictive association between fear of COVID-19 and emotional distress (depression, anxiety, and stress) in frontline and non-frontline nurses. To explore the mediating role of socio-demographic features. Correlational cross-sectional research design was implied. A total of 500 on-duty male and female, frontline and non-frontline, nurses were included from five major hospitals in Gujrat (Aziz Bhatti Shaheed Hospital, City Hospital, Doctors Hospital, Akram Hospital, and Gujrat Hospital). Fear of COVID-19 scale and the Urdu version of depression, anxiety, and stress scale - 21 (DASS-21) were used to measure variables of interest. Descriptive statistics, structural equation modeling (SEM), linear regression, and -test were carried out using Statistical Package for Social Sciences (SPSS) 21. Structural equation modeling (SEM) revealed a significant predictive link between fear of COVID-19 and depression, anxiety, and stress (goodness of model fit; NFI = 0.93, GFI = 0.914, AGFI = 0.93, CFI = 0.936, and IFI = 0.936). Furthermore, a significant mediating effect of certain demographic features was discovered by SEM (CMIN/DF = 1.11, NFI = 0.94, TLI = 0.98, GFI = 0.08, AGFI = 0.93, RMSEA = 0.029, CFI = 0.99, and IFI = 0.99). Results of linear regression analysis also revealed a momentous predictive association between fear of COVID-19 and emotional distress ( = 0.860). In comparative analysis, the results of t-test explored the statistical significant difference in fear of COVID-19 and emotional distress between frontline (mean = 25.775, 36.147 and SD = 1.75, 2.23) and non-frontline nurses (mean = 21.702, 27.353 and SD = 4.607, 10.212), with =7.111, 6.92. Managing the mediating effect of demographic characteristics and reducing the fear of COVID-19 can help nurses to overcome emotional distress, such as depression, anxiety, and stress. Further, this will increase the productivity among nurses.
确定一线和非一线护士对新冠病毒的恐惧与情绪困扰(抑郁、焦虑和压力)之间的预测关联。探讨社会人口学特征的中介作用。采用相关性横断面研究设计。从古吉拉特的五家主要医院(阿齐兹·巴蒂·谢赫德医院、市立医院、医生医院、阿克拉姆医院和古吉拉特医院)纳入了500名在职男女护士,包括一线和非一线护士。使用对新冠病毒的恐惧量表以及抑郁、焦虑和压力量表-21(DASS-21)的乌尔都语版本来测量感兴趣的变量。使用社会科学统计软件包(SPSS)21进行描述性统计、结构方程建模(SEM)、线性回归和t检验。结构方程建模(SEM)显示对新冠病毒的恐惧与抑郁、焦虑和压力之间存在显著的预测联系(模型拟合优度;NFI = 0.93,GFI = 0.914,AGFI = 0.93,CFI = 0.936,IFI = 0.936)。此外,结构方程建模发现某些人口学特征具有显著的中介作用(CMIN/DF = 1.11,NFI = 0.94,TLI = 0.98,GFI = 0.08,AGFI = 0.93,RMSEA = 0.029,CFI = 0.99,IFI = 0.99)。线性回归分析结果还显示对新冠病毒的恐惧与情绪困扰之间存在显著的预测关联(= 0.860)。在比较分析中,t检验结果探讨了一线护士(均值 = 25.775,36.147;标准差 = 1.75,2.23)和非一线护士(均值 = 21.702,27.353;标准差 = 4.607,10.212)在对新冠病毒的恐惧和情绪困扰方面的统计学显著差异,t值分别为7.111和6.92。控制人口学特征的中介作用并减少对新冠病毒的恐惧有助于护士克服情绪困扰,如抑郁、焦虑和压力。此外,这将提高护士的工作效率。