University of Amsterdam, Academic Medical Center, Department of Psychiatry, Meibergdreef 5, 1105 AZ Amsterdam, The Netherlands.
University of Amsterdam, Department of Psychology, Psychological Methods, Nieuwe Achtergracht 129-B, 1018 WT Amsterdam, The Netherlands.
Schizophr Res. 2017 Nov;189:75-83. doi: 10.1016/j.schres.2017.02.018. Epub 2017 Feb 22.
Current diagnostic systems mainly focus on symptoms needed to classify patients with a specific mental disorder and do not take into account the variation in co-occurring symptoms and the interaction between the symptoms themselves. The innovative network approach aims to further our understanding of mental disorders by focusing on meaningful connections between individual symptoms of a disorder and has thus far proven valuable insights to psychopathology. The aims of current study were to I) construct a symptom network and investigate interactions between a wide array of psychotic symptoms; II) identify the most important symptoms within this network and III) perform an explorative shortest pathway analysis between depressive and delusional symptoms. We analyzed interview data from n=408 male patients with non-affective psychosis using the Comprehensive Assessment of Symptoms and History (CASH). A network structure of 79 symptoms was computed to explore partial correlations between positive, negative, catatonia and affective symptoms. The resulting network showed strong connectivity between individual symptoms of the CASH, both within- and between-domains. Most central symptoms included 'loss of interest', 'chaotic speech', 'inability to enjoy recreational interest in activities', 'inability to form or maintain relationships with friends' and 'poverty of content of speech'. The shortest pathway analysis between depressive and delusional symptoms displayed an important role for 'persecutory delusions'. In conclusion, this study showed that individual psychotic symptoms are meaningfully related to each other not only within their own cluster, but also between different clusters and that important information may be acquired by investigating interactions at a symptom level.
当前的诊断系统主要关注用于对特定精神障碍患者进行分类的症状，而没有考虑到同时存在的症状的变化和症状本身之间的相互作用。创新的网络方法旨在通过关注疾病的个体症状之间的有意义的联系来进一步了解精神障碍，迄今为止已被证明对精神病理学有价值的见解。本研究的目的是：i）构建症状网络并研究广泛的精神病症状之间的相互作用；ii）确定该网络中的最重要症状；iii）进行抑郁症状和妄想症状之间的探索性最短路径分析。我们使用综合症状和病史评估（CASH）分析了 n=408 名男性非情感性精神病患者的访谈数据。计算了 79 个症状的网络结构，以探索阳性、阴性、紧张症和情感症状之间的偏相关。结果网络显示了 CASH 中个体症状之间的强连接性，包括域内和域间。最中心的症状包括“兴趣丧失”、“言语混乱”、“无法享受活动的娱乐兴趣”、“无法与朋友建立或维持关系”和“言语内容匮乏”。抑郁症状和妄想症状之间的最短路径分析显示，“迫害妄想”起着重要作用。总之，这项研究表明，个体精神病症状不仅在其自身的集群内，而且在不同的集群之间也具有有意义的相互关系，通过研究症状层面的相互作用可以获得重要信息。
