Chavez-Baldini UnYoung, Verweij Karin, de Beurs Derek, Bockting Claudi, Lok Anja, Sutterland Arjen L, van Rooijen Geeske, van Wingen Guido, Denys Damiaan, Vulink Nienke, Nieman Dorien
Department of Psychiatry, Amsterdam University Medical Center, University of Amsterdam, The Netherlands.
Department of Epidemiology, Netherlands Institute of Mental Health and Addiction (Trimbos Institute), The Netherlands.
BJPsych Open. 2022 Jun 27;8(4):e116. doi: 10.1192/bjo.2022.516.
Recent paradigm shifts suggest that psychopathology manifests through dynamic interactions between individual symptoms.
To investigate the longitudinal relationships between symptoms in a transdiagnostic sample of patients with psychiatric disorders.
A two-wave, cross-lagged panel network model of 15 nodes representing symptoms of depression, (social) anxiety and attenuated psychotic symptoms was estimated, using baseline and 1-year follow-up data of 222 individuals with psychiatric disorders. Centrality indices were calculated to determine important predictors and outcomes.
Our results demonstrated that the strongest relationships in the network were between (a) more suicidal ideation predicting more negative self-view, and (b) autoregressive relationships of social anxiety symptoms positively reinforcing themselves. Negative self-view was the most predictable node in the network as it had the highest 'in-expected influence' centrality, and may be an important transdiagnostic outcome symptom.
The results give insight into longitudinal interactions between symptoms, which interact in ways that do not adhere to broader diagnostic categories. Our results suggest that self-view can also be a transdiagnostic outcome of psychopathology rather than just a predictor, as is normally posited, and may especially have an important relationship with suicidal ideation. Overall, our study demonstrates the dynamic complexity of psychopathology, and further supports the importance of investigating symptom interactions of different psychopathological dimensions over time and across disorders.
最近的范式转变表明,精神病理学通过个体症状之间的动态相互作用表现出来。
研究精神障碍患者跨诊断样本中症状之间的纵向关系。
使用222名精神障碍患者的基线数据和1年随访数据,估计了一个由15个节点组成的两波交叉滞后面板网络模型,这些节点代表抑郁、(社交)焦虑和精神病性症状减弱。计算中心性指标以确定重要的预测因素和结果。
我们的结果表明,网络中最强的关系存在于:(a)更多的自杀意念预示着更消极的自我认知,以及(b)社交焦虑症状的自回归关系会正向强化自身。消极自我认知是网络中最可预测的节点,因为它具有最高的“预期内影响”中心性,可能是一个重要的跨诊断结果症状。
这些结果揭示了症状之间的纵向相互作用,它们以不符合更广泛诊断类别的方式相互作用。我们的结果表明,自我认知也可以是精神病理学的一个跨诊断结果,而不仅仅是一个预测因素,正如通常所假设的那样,并且可能尤其与自杀意念有重要关系。总体而言,我们的研究证明了精神病理学的动态复杂性,并进一步支持了随着时间推移和跨疾病研究不同精神病理维度症状相互作用的重要性。