Wu Peiyi, Wang Yucheng, Zhou Yang, Xu Yixiao, Zhang Huanrui, Li Zijia, Tang Yanqing
Department of Psychiatry, Shengjing Hospital of China Medical University, 155 Nanjing North Street, Shenyang, 114000, Liaoning, China.
School of Public Health, China Medical University, Shenyang, China.
Eur Arch Psychiatry Clin Neurosci. 2025 Apr 23. doi: 10.1007/s00406-025-02011-1.
This study utilized network analysis to explore the intricate relationships between anxiety, depression, and quality of life in a cohort of hospitalized schizophrenia patients. Through a cross-sectional design, the investigation aimed to identify key symptoms and bridge connections to inform tailored clinical interventions and improve patient well-being. Symptom severity was measured using the Hamilton Depression Rating Scale, Hamilton Anxiety Rating Scale, and Schizophrenia Quality of Life Scale, with network analysis elucidating central nodes and bridging symptoms within the patient sample of 1328 individuals. Findings revealed psychic anxiety, insomnia, and depressed mood as pivotal within the network, significantly impacting overall symptomatology and quality of life. Furthermore, symptoms such as tension and fears were identified as essential connectors among different symptom domains, highlighting potential intervention targets. The study underscores the complex dynamics between anxiety, depression, and quality of life in schizophrenia, advocating for an integrated treatment approach that focuses on critical symptoms to enhance overall well-being. This approach suggests a paradigm shift towards personalized care in schizophrenia management, aiming to optimize outcomes by addressing the root of symptom networks.
本研究利用网络分析方法，探讨了一组住院精神分裂症患者中焦虑、抑郁和生活质量之间的复杂关系。通过横断面设计，该调查旨在识别关键症状并建立联系，为量身定制的临床干预提供依据，以改善患者的健康状况。使用汉密尔顿抑郁评定量表、汉密尔顿焦虑评定量表和精神分裂症生活质量量表来测量症状严重程度，网络分析揭示了1328名患者样本中的中心节点和桥梁症状。研究结果显示，精神性焦虑、失眠和抑郁情绪在网络中起关键作用，对整体症状和生活质量有显著影响。此外，紧张和恐惧等症状被确定为不同症状领域之间的重要连接点，突出了潜在的干预目标。该研究强调了精神分裂症中焦虑、抑郁和生活质量之间的复杂动态关系，主张采用综合治疗方法，关注关键症状以提高整体健康水平。这种方法表明在精神分裂症管理中向个性化护理的范式转变，旨在通过解决症状网络的根源来优化治疗效果。
