Data_Sheet_1_Night shifts, insomnia, anxiety, and depression among Chinese nurses during the COVID-19 pandemic remission period: A network approach.docx
收藏frontiersin.figshare.com2023-06-01 更新2025-03-25 收录
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https://frontiersin.figshare.com/articles/dataset/Data_Sheet_1_Night_shifts_insomnia_anxiety_and_depression_among_Chinese_nurses_during_the_COVID-19_pandemic_remission_period_A_network_approach_docx/21672374/1
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BackgroundThe outbreak of the COVID-19 pandemic imposed a heavy workload on nurses with more frequent night shifts, which led to higher levels of insomnia, depression, and anxiety among nurses. The study aimed to describe the symptom-symptom interaction of depression, anxiety, and insomnia among nurses and to evaluate the impact of night shifts on mental distress via a network model.MethodsWe recruited 4,188 nurses from six hospitals in December 2020. We used the Insomnia Severity Index, Patient Health Questionnaire-9, and Generalized Anxiety Disorder Scale-7 to assess insomnia, depression, and anxiety, respectively. We used the gaussian graphical model to estimate the network. Index expected influence and bridge expected influence was adapted to identify the central and bridge symptoms within the network. We assessed the impact of night shifts on mental distress and compared the network structure based on COVID-19 frontline experience.ResultsThe prevalence of depression, anxiety, and insomnia was 59, 46, and 55%, respectively. Nurses with night shifts were at a higher risk for the three mental disorders. “Sleep maintenance” was the central symptom. “Fatigue,” “Motor,” “Restlessness,” and “Feeling afraid” were bridge symptoms. Night shifts were strongly associated with sleep onset trouble. COVID-19 frontline experience did not affect the network structure.Conclusion“Sleep maintenance,” “Fatigue,” “Motor,” and “Restlessness” were important in maintaining the symptom network of anxiety, depression, and insomnia in nurses. Further interventions should prioritize these symptoms.
背景:COVID-19疫情的爆发对护士的工作量造成了巨大压力,导致夜班频率增加,进而使护士群体中失眠、抑郁和焦虑的水平显著上升。本研究旨在描述护士群体中抑郁、焦虑和失眠之间的症状交互作用,并通过网络模型评估夜班对心理压力的影响。方法:我们于2020年12月从六家医院招募了4,188名护士。分别采用失眠严重程度指数、患者健康问卷-9和广泛性焦虑症量表-7对失眠、抑郁和焦虑进行评估。利用高斯图形模型估计网络结构。通过指数预期影响和桥接预期影响识别网络中的核心和桥梁症状。评估夜班对心理压力的影响,并比较基于COVID-19前线经验的网络结构。结果:抑郁、焦虑和失眠的患病率分别为59%、46%和55%。有夜班的护士患三种心理障碍的风险更高。“睡眠维持”是核心症状。“疲劳”、“运动”、“不安”和“感到害怕”是桥梁症状。夜班与睡眠开始困难有强烈的关联。COVID-19前线经验不影响网络结构。结论:“睡眠维持”、“疲劳”、“运动”和“不安”对于维持护士群体中焦虑、抑郁和失眠的症状网络至关重要。进一步干预应优先考虑这些症状。
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