中国四个省市护理人员心理健康影响因素的多水平分析
Multilevel analysis of factors influencing mental health of nursing staff in four provinces in China
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摘要:
背景 护理人员在工作环境中常暴露于多种职业危险因素，如长工时、高工作负荷等，可能对心理健康方面产生负面影响，且这些危险因素可能在不同水平上并非随机分布。
目的 利用多水平模型分析探讨护理人员心理健康水平的影响因素在不同水平上的效应变化。
方法 通过方便抽样，在2018—2021年间对中国上海市、浙江省、广西壮族自治区、新疆维吾尔自治区四个省市的护理人员进行了横断面调查。采用问卷自我报告的方法收集数据，采用SF-12生存质量量表中心理领域得分评价护理人员心理健康水平，并收集其相关影响因素。个体水平影响因素包括性别、体重指数（BMI）、吸烟情况、饮酒情况、工龄、肌肉骨骼疾患疼痛强度、每周工作时长，区域水平影响因素包括各省市国内生产总值（GDP）水平。基于多水平分析对个体和区域水平影响因素构建多水平模型，使用偏差值进行模型的拟合优度检验。同时使用传统的广义线性模型进行建模，并比较多水平模型与传统模型。
结果 本研究回收问卷567份，合格率为80.08%。多水平模型结果显示：区域变量对心理领域得分贡献度达12.1%，在区域水平的影响因素中，GDP与护理人员心理领域得分呈负相关，调整后OR值（AOR）为−0.53（95%CI：−0.66~−0.28）；在个体水平的影响因素中，女性比男性心理领域得分更低（AOR=−3.25，95%CI：−4.73~−0.35），工龄越长心理领域得分越高（AOR=0.11，95%CI：0.06~0.20），而每周工作时长（AOR=−0.10，95%CI：−0.14~−0.03）、肌肉骨骼疾患疼痛强度（AOR=−0.05，95%CI：−0.06~−0.03）与心理领域得分呈负相关。广义线性模型结果中纳入的影响因素与多水平模型相同，但多水平模型影响因素AOR值的95%CI更窄，且多水平模型的偏差值最小，拟合优度更好。
结论 护理人员心理健康不仅受到个体水平因素的影响，也受到区域水平上因素的影响，针对不同层次影响因素可以采取不同层面的干预措施以改善其心理健康。
Abstract:Background Nursing staff are often exposed to a variety of occupational risk factors in the working environment, such as long working hours and heavy workload, which associated with adverse mental health outcomes. And these factors may not be randomly distributed across different levels.
Objective To explore mental health risk factors of nursing staff by multilevel analysis.
Methods A cross-sectional survey of nursing staff in Shanghai Municipality, Zhejiang Province, Guangxi Zhuang Autonomous Region, and Xinjiang Uygur Autonomous Region was conducted through convenience sampling from 2018 to 2021. Data were collected by self-report questionnaires. The mental component summaries of 12-Iitem Short Form Health Survey were used to evaluate the mental health status of nursing staff, and related factors were collected atindividual level, including gender, body mass index (BMI), smoking status, drinking status, working years, pain intensity of musculoskeletal disorders, and working hours per week, and at regional level, including gross domestic product (GDP) level of each province. A two-level model was established by incorporating both individual and regional factors, and deviance was used to test the goodness of fit of the model. A traditional generalized linear model was also established, and then compared with the multilevel model.
Results A total of 567 nurses participated in this study, and the valid rate of questionnaire was 80.08%. The results of the multilevel model showed that the regional factor contributed 12.1% to the mental component summaries. As to the regional factor, GDP was negatively correlated with mental health of nursing staff, the adjusted OR (AOR) was −0.53 (95%CI: −0.66-−0.28). Among the factors at individual level, the mental component summaries of females were lower than those of males (AOR=−3.25, 95%CI: −4.73-−0.35); the longer the working years, the higher the mental health score (AOR=0.11, 95%CI: 0.06-0.20); working hours per week (AOR=−0.10, 95%CI: −0.14-−0.03) and pain intensity of musculoskeletal disorders ( AOR=−0.05, 95%CI: −0.06-−0.03) were negatively correlated with mental component summaries. The results of the generalized linear model included the same factors as the multilevel model, but the 95% CIs of AOR of the factors in the multilevel model were narrower, and the deviation value of the multilevel model was the smallest, indicating that the goodness of fit of the multilevel model was better than that of the traditional linear model.
Conclusion The mental health of nursing staff is not only affected by individual level factors, but also affected by regional level factors. It suggests that combining different levels of intervention measures can upscale the effect of improving mental health in nursing staff.
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