| Literature DB >> 28237606 |
Geeske van Rooijen1, Adela-Maria Isvoranu2, Carin J Meijer3, Claudia D van Borkulo4, Henricus G Ruhé5, Lieuwe de Haan6.
Abstract
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.Entities:
Keywords: CASH; Network analysis; Non-affective psychotic disorders; Psychosis spectrum; Schizophrenia; Shortest pathway analysis
Mesh:
Year: 2017 PMID: 28237606 DOI: 10.1016/j.schres.2017.02.018
Source DB: PubMed Journal: Schizophr Res ISSN: 0920-9964 Impact factor: 4.939