姜文婧, 刘秋润, 李俊, 钟英, 张翠翠, 刘文莉, 刘曦, 廖常菊. 负性情绪在临床一线医务人员社会支持与消极应对中的中介作用[J]. 职业卫生与应急救援, 2021, 39(4): 382-387. DOI: 10.16369/j.oher.issn.1007-1326.2021.04.004
引用本文: 姜文婧, 刘秋润, 李俊, 钟英, 张翠翠, 刘文莉, 刘曦, 廖常菊. 负性情绪在临床一线医务人员社会支持与消极应对中的中介作用[J]. 职业卫生与应急救援, 2021, 39(4): 382-387. DOI: 10.16369/j.oher.issn.1007-1326.2021.04.004
JIANG WenJing, LIU Qiurun, LI Jun, ZHONG Ying, ZHANG Cuicui, LIU Wenli, LIU Xi, LIAO Changju. Mediating role of negative emotion in social support and negative coping of medical staff[J]. Occupational Health and Emergency Rescue, 2021, 39(4): 382-387. DOI: 10.16369/j.oher.issn.1007-1326.2021.04.004
Citation: JIANG WenJing, LIU Qiurun, LI Jun, ZHONG Ying, ZHANG Cuicui, LIU Wenli, LIU Xi, LIAO Changju. Mediating role of negative emotion in social support and negative coping of medical staff[J]. Occupational Health and Emergency Rescue, 2021, 39(4): 382-387. DOI: 10.16369/j.oher.issn.1007-1326.2021.04.004

负性情绪在临床一线医务人员社会支持与消极应对中的中介作用

Mediating role of negative emotion in social support and negative coping of medical staff

  • 摘要:
      目的  探讨新型冠状病毒肺炎抗疫一线医务人员的社会支持、负性情绪与消极应对的关系。
      方法  采用一般资料调查表、社会支持量表、突发公共卫生事件心理量表和简易应对方式量表对四川省某市新型冠状病毒肺炎唯一定点医院1 372名一线抗疫医务人员进行横断面调查。采用Pearson相关性分析和多元线性回归分析检验变量之间的关系,采用Bootstrap方法检验负性情绪在社会支持和消极应对中的中介效应。
      结果  医务人员社会支持评分为(41.51 ±9.13)分,负性情绪评分为(0.52 ±0.40)分,消极应对评分为(0.80 ±0.56)分。年龄越大、工作年限越久的医务人员所获得的社会支持越多,所表现出的负性情绪越低,也更不容易采取消极应对的方式(P < 0.05)。女性医务人员比男性医务人员更容易出现负性情绪和采取消极应对的方式(P < 0.05)。护士的负性情绪要高于医生和医技人员(P < 0.05)。社会支持与负性情绪(r=-0.172,P < 0.01)、消极应对(r=-0.082,P < 0.01)呈负相关,负性情绪与消极应对呈正相关(r=0.427,P < 0.01)。社会支持得分负向预测负性情绪(β=-0.306,P < 0.01)和消极应对(β=-0.077,P < 0.01)。社会支持对负性情绪的效应显著β=-0.181,95%置信区间为(-0.238~-0.124),t=-6.278,P < 0.001;负性情绪对消极应对的效应显著β=0.188,95%置信区间(0.166~0.210),t=16.733,P < 0.001;社会支持对消极应对的直接效应不显著β=-0.004,95%置信区间为(-0.028~0.020),t=-0.733,P=0.760。负性情绪在社会支持与消极应对中起完全中介作用,中介效应值占总效应的89.5%。
      结论  社会支持通过负性情绪间接地对抗疫一线医务人员的消极应对行为产生影响。应该加强医务人员的社会支持,从而使其在工作中采取更积极的应对方式。

     

    Abstract:
      Objective  To investigate the relationship between social support, negative emotion, and negative coping of first-line medical staff against COVID-19.
      Methods  Totally 1 372 first-line anti-epidemic medical staff were surveyed with general data questionnaire, the Social Support Scale, the Public Health Emergency Psychological Scale, and the Simple Coping Style Scale in a sole designated hospital for COVID-19 treatment in Sichuan Province. Pearson correlation analysis and multiple linear regression analysis were used to test the relationship between variables. Bootstrap method was used to test the mediating effect of negative emotion in social support and negative emotion.
      Results  The social support score of medical staff was 41.51±9.13. The score of negative emotion was 0.52±0.40. The negative response score was 0.80±0.56. The older the age and the longer the working time, the more social support they received, the lower the negative temperament they showed, and they were less likely to adopt negative coping styles(P < 0.05). Female medical staff were more likely to have negative emotions and adopt negative coping styles than male medical staff(P < 0.05). The negative emotion of nurses was much higher than that of doctors and medical technicians(P < 0.05). Social support was negatively correlated with negative emotions(r=-0.172, P < 0.01) and negative coping (r=-0.082, P < 0.01), while negative emotions were significantly positively correlated with negative coping (r=0.427, P < 0.01). Social support negatively predicted negative emotions (β=-0.306, P < 0.01) and negative coping(β=-0.077, P < 0.01). Social support had a significant effect on negative emotionsβ=-0.181, 95% confidence interval(-0.238﹣-0.124), t=-6.278, P < 0.001;Negative emotion had a significant effect on negative copingβ=0.188, 95% confidence interval(0.166-0.210), t=16.733, P < 0.001;The direct effect of social support on negative coping was not significantβ=-0.004, 95% confidence interval(-0.028-0.020), t=-0.733, P=0.760. Negative emotion played a complete mediating role in social support and negative coping, and the mediating effect accounted for 89.3% of the total effect.
      Conclusions  Social support indirectly affects the negative coping behavior of the first-line medical staff through negative emotions. We should strengthen the social support of medical staff, so that they can take a more positive coping style in their work.

     

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