Hou Xiumei, Wang Yan, Wu Yang, Shen Qinge, Liu Ping, Xu Yunshuai, Dong Jicheng, Wang Yaping, Chen Min, Cui Jian
Department of Psychiatry, Shandong Daizhuang Hospital, Jining, China.
Department of Psychiatry, School of Mental Health, Jining Medical University, Jining, China.
Front Psychiatry. 2025 Jul 18;16:1586086. doi: 10.3389/fpsyt.2025.1586086. eCollection 2025.
Depression and cognitive impairment among healthcare workers significantly affect their life satisfaction (LS). This study used network analysis to explore the associations between depression, cognitive symptoms, and LS in healthcare workers.
A total of 655 healthcare workers were assessed using the Patient Health Questionnaire (PHQ-9), the Perceived Deficits Questionnaire-Depression (PDQ-D), and the Quality of Life Enjoyment and Satisfaction Questionnaire-Short Form (Q-LES-Q-SF). Regularized partial correlation network analysis was conducted, focusing on the strength values and predictability of each item in the network. The R software was used for statistical analysis and visualization of the network.
The average PHQ-9 depression score was 4.79, while the mean cognitive symptoms score was 15.38 (Our score range for all participants: PDQ-D 0 - 70; PHQ-9 0 - 27). Network analysis revealed that PDQ12 ("Trouble getting started"), PDQ13 ("Drifting"), and PDQ17 ("Remembering numbers") were the central symptoms of the entire depression-cognition network. PHQ1 ("Anhedonia"), PHQ7 ("Concentration"), and PDQ 13 ("Drifting") were the most critical bridge symptoms connecting depression and cognition. The three symptoms of PHQ2 ("Sad Mood"), PHQ4 ("Fatigue"), and PDQ 13 ("Drifting") had the strongest negative correlations with LS. Gender showed no significant relationship with global network strength, edge weight distribution, or individual edge weights.
This network analysis identified several central symptoms, including "Trouble getting started", "Drifting", and "Remembering numbers". It also identified bridge symptoms such as "Anhedonia", "Concentration", and "Drifting". These findings provide important evidence for the development of targeted interventions. Furthermore, measures such as improving emotional management, increasing rest periods, and providing psychological support may help alleviate fatigue and low mood, enhance attentional functioning, and ultimately improve life satisfaction among healthcare workers.
医护人员的抑郁和认知障碍会显著影响他们的生活满意度（LS）。本研究采用网络分析方法来探究医护人员抑郁、认知症状与生活满意度之间的关联。
共655名医护人员接受了患者健康问卷（PHQ - 9）、感知缺陷问卷 - 抑郁版（PDQ - D）和生活质量享受与满意度问卷简版（Q - LES - Q - SF）的评估。进行了正则化偏相关网络分析，重点关注网络中各项目的强度值和可预测性。使用R软件进行网络的统计分析和可视化。
PHQ - 9抑郁得分平均为4.79，而认知症状平均得分为15.38（所有参与者的得分范围：PDQ - D为0 - 70；PHQ - 9为0 - 27）。网络分析显示，PDQ12（“难以开始”）、PDQ13（“注意力不集中”）和PDQ17（“数字记忆困难”）是整个抑郁 - 认知网络的核心症状。PHQ1（“快感缺失”）、PHQ7（“注意力不集中”）和PDQ13（“注意力不集中”）是连接抑郁和认知的最关键的桥梁症状。PHQ2（“情绪低落”）、PHQ4（“疲劳”）和PDQ13（“注意力不集中”）这三个症状与生活满意度的负相关性最强。性别与整体网络强度、边权重分布或单个边权重均无显著关系。
该网络分析确定了几个核心症状，包括“难以开始”、“注意力不集中”和“数字记忆困难”。还确定了如“快感缺失”、“注意力不集中”等桥梁症状。这些发现为制定有针对性的干预措施提供了重要证据。此外，改善情绪管理、增加休息时间和提供心理支持等措施可能有助于减轻疲劳和低落情绪，增强注意力功能，最终提高医护人员的生活满意度。
