青年男性抑郁症状的网络分析研究

Network Analysis Study of Depressive Symptoms in Young Males

摘要: 目的：以青年男性为研究对象，探究其抑郁症状的网络特征并确认核心症状，从而为更精准有效的干预提供潜在干预靶点。方法：对778名青年男性的健康问卷抑郁症状群量表进行正则化偏相关网络分析，尤其关注网络中各抑郁症状节点的预期影响。使用软件R对网络进行分析和可视化。结果：在抑郁症状网络中，项目“兴趣缺失”和“心境抑郁”之间、“兴趣缺失”和“疲倦”之间存在最强关联。“兴趣缺失”、“疲倦”和“心境抑郁”预期影响最大。症状网络节点预期影响的相关稳定性系数为0.75，表明其具有足够的稳定性。结论：本研究首次运用网络分析法研究了青年男性抑郁症状的网络特征，结果表明“兴趣缺失”、“疲倦”和“心境抑郁”是抑郁网络的核心症状。考虑以这些关键症状为主要干预靶点，可能会最大程度地降低整个抑郁症状网络的严重程度，从而更有效地改善青年男性的抑郁程度。

Abstract: Objective: The study aims to explore the network structure of depressive symptoms in young males and identify the core items to provide potential targets for future intervention. Methods: Regularized partial correlation network was used to explore the complex relations among items of Patients’ Health Questionnaire Depression Scale-9 item (PHQ-9) in 778 Chinese young males, with special attention to the expected impact of each symptom in the network. The network analysis and visualization were conducted in Software R. Results: In the depressive symptoms network, the edges between “Anhedonia” and “Sad mood” and between “Anhedonia” and “fatigue” were strongest. Item “Anhedonia”, “Fatigue”, and “Sad mood” have the highest expected influence in the network. In addition, the correlation stability coefficient of the expected influence was 0.75, indicating that the network has enough stability. Conclusion: The regularized partial correlation network was utilized first to explore the complex relationships among young males’ depressive symptoms in this study. The results showed that the “Anhedonia”, “Fatigue”, and “Sad mood” are the key symptoms. Targeting these symptoms may more effectively release the severity of the entire depressive symptom network and achieve greater therapeutic effects in depressive young males.