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精神卫生保健工作者焦虑与认知障碍的网络分析

Network analysis of anxiety and cognitive impairment among mental healthcare workers.

作者信息

Chen Ruirui, Yan Wei, Shen Qinge, Li Meng, Chen Min, Dong Jicheng, Wang Yaping, Zhao Xianxian, Cui Jian

机构信息

Clinical lab, Shandong Daizhuang Hospital, Jining, China.

Precision Medicine Laboratory, Shandong Daizhuang Hospital, Jining, China.

出版信息

Front Psychiatry. 2024 Aug 21;15:1393598. doi: 10.3389/fpsyt.2024.1393598. eCollection 2024.

Abstract

INTRODUCTION

With the rising demand for medical services and the associated burden, work-related stress and mental health issue have garnered increased attention among healthcare workers. Anxiety, cognitive impairment, and their comorbidities severely impact the physical and mental health as well as the work status of healthcare workers. The network analysis method was used to identify the anxiety and cognitive impairment among mental healthcare workers using the Generalized Anxiety Disorder Scale (GAD-7) and the Perceived Deficit Questionnaire for Depression (PDQ-D). We sought to identify the core symptoms associated with the comorbidity of anxiety and cognitive impairment in mental healthcare workers.

METHODS

The study was conducted by Shandong Daizhuang Hospital and Qingdao Mental Health Center in China from September 13, 2022, to October 25, 2022, involving a total of 680 healthcare workers as participants. GAD-7 and PDQ-D were utilized to assess anxiety and cognitive impairment, respectively. Regularized partial correlation network analysis was employed to examing the expected influence and predictability of each item within the network. Statistical analysis and visualization of the network were performed using R software.

RESULTS

The mean total score for anxiety was 3.25, while the mean total score for cognitive symptoms was 15.89. PDQ17 "Remembering numbers", PDQ12 "Trouble get started" and PDQ20 "Trouble make decisions" emerged as central symptoms in the anxiety-cognition network. GAD6 "Irritable", GAD5 "Restlessness" and GAD1 "Nervousness or anxiety" were identified as the most critical bridge symptoms connecting anxiety and cognition. Gender was found to be unrelated to the global strength of the network, edge weight distribution, or individual edge weights.

CONCLUSION

Utilizing central and bridge symptoms (i.e., Remembering numbers, Trouble get started, Trouble make decisions, Irritable, Restlessness and Nervousness or anxiety) as primary intervention points may aid in mitigating the serious health consequences of anxiety, cognitive impairment, and comorbidities anxiety and cognitive impairment for mental healthcare workers.

摘要

引言

随着对医疗服务需求的不断增加以及随之而来的负担,工作相关压力和心理健康问题在医护人员中受到了越来越多的关注。焦虑、认知障碍及其合并症严重影响医护人员的身心健康以及工作状态。本研究采用网络分析方法,使用广泛性焦虑障碍量表(GAD-7)和抑郁感知缺陷问卷(PDQ-D)来识别精神科医护人员中的焦虑和认知障碍。我们试图确定与精神科医护人员焦虑和认知障碍合并症相关的核心症状。

方法

本研究由中国山东戴庄医院和青岛市精神卫生中心于2022年9月13日至2022年10月25日进行,共有680名医护人员参与。分别使用GAD-7和PDQ-D评估焦虑和认知障碍。采用正则化偏相关网络分析来检验网络中每个项目的预期影响和可预测性。使用R软件进行网络的统计分析和可视化。

结果

焦虑的平均总分是3.25,而认知症状的平均总分是15.89。PDQ17“记住数字”、PDQ12“难以开始”和PDQ20“难以做出决定”成为焦虑-认知网络中的核心症状。GAD6“易怒”、GAD5“坐立不安”和GAD1“紧张或焦虑”被确定为连接焦虑和认知的最关键的桥梁症状。发现性别与网络的全局强度、边权重分布或单个边权重无关。

结论

将核心症状和桥梁症状(即记住数字、难以开始、难以做出决定、易怒、坐立不安和紧张或焦虑)作为主要干预点,可能有助于减轻焦虑、认知障碍以及焦虑和认知障碍合并症对精神科医护人员造成的严重健康后果。

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