Multilevel analysis of factors influencing mental health of nursing staff in four provinces in China
- VernacularTitle:中国四个省市护理人员心理健康影响因素的多水平分析
- Author:
Mengshuang LIU
1
;
Kezhi JIN
1
;
Siyi WANG
1
;
Ying SHEN
2
Author Information
- Publication Type:Selectedarticle
- Keywords: nursing staff; mental health; multilevel model; musculoskeletal disorders
- From: Journal of Environmental and Occupational Medicine 2022;39(6):639-644
- CountryChina
- Language:Chinese
- 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.
