Network Analysis of Sleep Quality and Anxiety of First-Line Medical Staff in Epidemic Prevention
10.12026/j.issn.1001-8565.2023.02.09
- VernacularTitle:抗疫一线医护人员睡眠质量与焦虑网络分析
- Author:
Yao ZHANG
1
;
Lin WU
2
;
Yijun LI
2
;
Baojuan LI
3
;
Jian LIU
4
;
Jiaru SUI
2
;
He HUANG
2
Author Information
1. Military Medical Center, The First Affiliated Hospital of Air Force Medical University, Xi’an 710032, China
2. Department of Military Medical Psychology, Air Force Medical University, Xi’an 710032, China
3. Department of Military Biomedical Engineering, Air Force Medical University, Xi’an 710032, China
4. Support Center for Teaching and Research, Air Force Medical University, Xi’an 710032, China
- Publication Type:Journal Article
- Keywords:
COVID-19;
Medical Staff;
Sleep Quality;
Anxiety;
Network Analysis
- From:
Chinese Medical Ethics
2023;36(2):167-173
- CountryChina
- Language:Chinese
-
Abstract:
【Objective:】 To explore the network characteristics of sleep quality and anxiety in first-line medical staff fighting against COVID-19, further understand the relationship between sleep quality and anxiety, and provide basis for intervention. 【Methods:】 Using the convenient sampling method, this paper used the Pittsburgh Sleep Quality Index (PSQI) and Self Rating Anxiety Scale (SAS) to conduct a questionnaire survey on the front-line medical staff who fought against the epidemic during the COVID-19. Network analysis was used to construct sleep quality and anxiety network, and R language was used for statistical analysis and visualization. 【Results:】 In the network of sleep quality and anxiety of first-line medical staff fighting against COVID-19, "sleep disorder" and "sleep quality", "unfortunate premonition" and "inability to sit still", "syncope" and "hand and foot tingling" were highly related. "Fatigue", "dizziness" and "panic" had the highest expected influence. "Sleep quality", "sleep disorder" and "fatigue" had the highest bridge expected influence. The average predictability value of all nodes was 0.778. 【Conclusion:】 This paper used network analysis to explore the sleep quality and anxiety of first-line medical staff fighting against COVID-19 and found that there was a unique correlation path between them. Intervention against core symptoms can ameliorate anxiety and sleep problems to the great extent, and provide guidance for improving the physical and mental health.
