Department of Neuropsychiatry, Seoul National University Bundang Hospital, Seongnam 13620, Republic of Korea.
Department of Psychology, Kyungpook National University, Daegu 41566, Republic of Korea.
Medicina (Kaunas). 2023 Dec 24;60(1):32. doi: 10.3390/medicina60010032.
Depressive symptoms are prominent in both major depressive disorder (MDD) and bipolar disorder (BD). However, comparative research on the network structure of depressive symptoms in these two diagnostic groups has been limited. This study aims to compare the network structure of depressive symptoms in MDD and BD, providing a deeper understanding of the depressive symptomatology of each disorder. The Zung Self-Rating Depressive Scale, a 20-item questionnaire, was administered to assess the depressive symptoms in individuals with MDD ( = 322) and BD ( = 516). A network analysis was conducted using exploratory graph analysis (EGA), and the network structure was analyzed using regularized partial correlation models. To validate the dimensionality of the Zung SDS, principal component analysis (PCA) was adopted. Centrality measures of the depressive symptoms within each group were assessed, followed by a network comparison test between the two groups. In both diagnostic groups, the network analysis revealed four distinct categories, aligning closely with the PCA results. "Depressed affect" emerged as the most central symptom in both MDD and BD. Furthermore, non-core symptoms, "Personal devaluation" in MDD and "Confusion" in BD, displayed strong centrality. The network comparison test did not reveal significant differences in the network structure between MDD and BD. The absence of significant differences in the network structures between MDD and BD suggests that the underlying mechanisms of depressive symptoms may be similar across these disorders. The identified central symptoms, including "Depressed affect", in both disorders and the distinct non-core symptoms in each highlight the complexity of the depressive symptomatology. Future research should focus on validating these symptoms as therapeutic targets and incorporate various methodologies, including non-metric dimension reduction techniques or canonical analysis.
抑郁症状在重度抑郁症（MDD）和双相情感障碍（BD）中都很明显。然而，关于这两种诊断组别的抑郁症状网络结构的比较研究还很有限。本研究旨在比较 MDD 和 BD 中抑郁症状的网络结构，深入了解每种疾病的抑郁症状。
采用zung 自评抑郁量表（Zung Self-Rating Depressive Scale）对 MDD（n=322）和 BD（n=516）患者的抑郁症状进行评估。采用探索性图形分析（EGA）进行网络分析，并采用正则化偏相关模型分析网络结构。采用主成分分析（PCA）验证 Zung SDS 的维度。评估每个组内抑郁症状的中心性度量，然后对两组之间的网络进行比较测试。
在两个诊断组中，网络分析都揭示了四个不同的类别，与 PCA 结果非常吻合。“抑郁情绪”是 MDD 和 BD 中最中心的症状。此外，非核心症状“个人贬低”在 MDD 和“困惑”在 BD 中表现出很强的中心性。网络比较测试未发现 MDD 和 BD 之间网络结构的显著差异。
MDD 和 BD 之间网络结构没有显著差异表明，这些疾病中抑郁症状的潜在机制可能相似。在这两种疾病中，确定的核心症状，包括“抑郁情绪”，以及每种疾病中独特的非核心症状，突出了抑郁症状的复杂性。未来的研究应该集中验证这些症状作为治疗靶点，并采用各种方法，包括非度量维度减少技术或规范分析。
