疫情防控常态化期间温州一线医务人员心理健康状况及影响因素

Mental health status and related influencing factors of front-line medical staff in Wenzhou during regular epidemic prevention and control

目的:了解疫情防控常态化期间一线医务人员心理健康状况及其影响因素,为及时有效地开展相关心理健康预防与干预提供依据。方法:于2022年3至4月采用方便取样方法,通过问卷星对581名温州市一线抗疫医务人员在线施测一般资料问卷、工作压力量表、社会支持量表、工作-家庭冲突问卷、抑郁-焦虑-压力量表简版(DASS-21)以及失眠严重程度指数量表(ISI),共回收558份有效问卷。通过一般资料问卷、DASS-21量表以及ISI量表评估一线医务人员心理健康现状,并就人口学变量作差异比较;同时,利用逐步线性回归分析探索其心理健康的潜在影响因素。结果:所有受试的一线医务人员中,280人(50.18%)存在焦虑症状,272人(48.75%)存在抑郁症状,356人(63.80%)存在失眠问题。女性一线医务人员的焦虑得分显著高于男性(P<0.05);本科及以下学历、护士以及身体状况较差的一线医务人员的焦虑(P<0.01)、抑郁(P<0.05)与失眠(P<0.01)得分显著高于高学历、其他职业与身体状况较好者;工龄为3年及以下的一线医务人员的焦虑(P<0.001)、抑郁(P<0.001)及失眠(P<0.001)得分显著低于工龄更长者。逐步回归分析发现,身体状况较差(β=2.72,P<0.01;β=2.50,P<0.05;β=2.54,P<0.01)、工作压力较高(β=1.29,P<0.001;β=1.29,P<0.001;β=0.61,P<0.001)以及工作-家庭冲突较大(β=1.04,P<0.001;β=0.89,P<0.01;β=0.66,P<0.01)是疫情常态化期间一线医务人员焦虑、抑郁与失眠的风险性因素,较高的社会支持(β=-0.30,P<0.01;β=-0.51,P<0.001;β=-0.24,P<0.01)是三者的保护性因素;工龄为>3~5年(β=2.77,P<0.01)以及>5~10年(β=2.16,P<0.05)分别是抑郁和失眠的风险性因素;护士(β=-2.34,P<0.01;β=-1.39,P<0.05)是焦虑和失眠的高风险人群。结论:在疫情常态化时期需要高度关注一线医务人员的心理健康状况,建议政府带头联动多方,通过降低一线医务职业压力,充分发挥社会支持的正向作用,开设个性化心理援助等心理服务以完善一线医务人员的心理预防与干预体系。

Objective: To investigate medical staff’s mental health status and its influencing factors during regular epidemic prevention and control so as to provide sufficient evidence for timely and effective psychological prevention and intervention. Methods: From March to April 2022, 581 front-line medical staff in Wenzhou were included in this study by convenience sampling method. They completed the general information questionnaire,Occupational Stress Scale, Social Support Scale, Self-Assessment Work-Family Conflict Item, Depression Anxiety Stress Scale-21 Short Version and Insomnia Severity Index through online questionnaire survey platform. A total of 558 valid questionnaires were collected. The general information questionnaire, DASS-21 Scale and ISI Scale were used to evaluate the mental health status of front-line medical staff and demographic variables were compared among them. Besides, stepwise regression analysis was used to explore the potential influencing factors of mental health. Results: Of all the medical staff surveyed, 280(50.18%) had anxiety, 272(48.75%) had depression, and 356(63.80%) had symptoms of insomnia. Women had higher scores of anxiety than men(P<0.05);the scores of anxiety(P<0.01), depression(P<0.05) and insomnia(P<0.01) of nurses, those with a bachelor’s degree or below and those with poorer physical conditions were more severe than those with higher education and those with other occupations and better physical health;in addition, the scores of anxiety(P<0.001), depression(P<0.001) and insomnia(P<0.001) of those who worked less than 3 years were lower than those with longer service years.Stepwise regression analysis found that poor physical condition(β=2.72, P<0.01;β=2.50, P<0.05;β=2.54,P<0.01), higher level of occupational stress(β=1.29, P<0.001;β=1.29, P<0.001;β=0.61, P<0.001) and more intense work-family conflict(β=1.04, P<0.001;β=0.89, P<0.01;β=0.66, P<0.01) were risk factors of anxiety,depression and insomnia among front-line medical staff during the normalization of the epidemic, while higher level of social support(β=-0.30, P<0.01;β=-0.51, P<0.001;β=-0.24, P<0.01) was a protective factor of the three;working >3-5 years(β=2.77, P<0.01) and >5-10 years(β=2.16, P<0.05) were risk factors for depression and insomnia, respectively;and nurses were at high risk for anxiety and insomnia(β=-2.34, P<0.01;β=-1.39,P<0.05). Conclusion: It is necessary to pay closer attention to the front-line medical staff’s mental health status during regular epidemic prevention and control. And it is recommended that governments at all levels take the lead in negotiating various departments and giving full play to the positive role of social support by reducing occupational stress of the front-line medical staff, and providing psychological services such as personalized psychological assistance to improve the psychological prevention and intervention system.