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. 2021 Jul 8;47(4):1018-1028.
doi: 10.1093/schbul/sbaa187.

Obsessive-Compulsive Symptoms and Other Symptoms of the At-risk Mental State for Psychosis: A Network Perspective

Hui Lin Ong  1 , Adela-Maria Isvoranu  1 , Frederike Schirmbeck  2   3 , Philip McGuire  4 , Lucia Valmaggia  5 , Matthew J Kempton  4 , Mark van der Gaag  6 , Anita Riecher-Rössler  7 , Rodrigo A Bressan  8 , Neus Barrantes-Vidal  9   10 , Barnaby Nelson  11   12 , G Paul Amminger  11 , Patrick McGorry  11   12 , Christos Pantelis  13 , Marie-Odile Krebs  14 , Merete Nordentoft  15 , Birte Glenthøj  16 , Stephan Ruhrmann  17 , Gabriele Sachs  18 , Bart P F Rutten  19 , Jim van Os  4   19   20 , Lieuwe de Haan  2   3 , Denny Borsboom  1 ; EU-GEI High Risk Study
Collaborators, Affiliations

Obsessive-Compulsive Symptoms and Other Symptoms of the At-risk Mental State for Psychosis: A Network Perspective

Hui Lin Ong et al. Schizophr Bull. .

Abstract

Background: The high prevalence of obsessive-compulsive symptoms (OCS) among subjects at Ultra-High Risk (UHR) for psychosis is well documented. However, the network structure spanning the relations between OCS and symptoms of the at risk mental state for psychosis as assessed with the Comprehensive Assessment of At Risk Mental States (CAARMS) has not yet been investigated. This article aimed to use a network approach to investigate the associations between OCS and CAARMS symptoms in a large sample of individuals with different levels of risk for psychosis.

Method: Three hundred and forty-one UHR and 66 healthy participants were included, who participated in the EU-GEI study. Data analysis consisted of constructing a network of CAARMS symptoms, investigating central items in the network, and identifying the shortest pathways between OCS and positive symptoms.

Results: Strong associations between OCS and anxiety, social isolation and blunted affect were identified. Depression was the most central symptom in terms of the number of connections, and anxiety was a key item in bridging OCS to other symptoms. Shortest paths between OCS and positive symptoms revealed that unusual thought content and perceptual abnormalities were connected mainly via anxiety, while disorganized speech was connected via blunted affect and cognitive change.

Conclusions: Findings provide valuable insight into the central role of depression and the potential connective component of anxiety between OCS and other symptoms of the network. Interventions specifically aimed to reduce affective symptoms might be crucial for the development and prospective course of symptom co-occurrence.

Keywords: anxiety; clinical high risk; depression; network analysis; obsessive-compulsive; psychosis; ultra-high risk.

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Figures

Fig. 1.
Fig. 1.
Network structure of 21 CAARMS symptoms. Item groups are differentiated by color. The color of the edge indicates the size of the association (blue for positive associations; red for negative associations). For a color version, see this figure online.
Fig. 2.
Fig. 2.
(Left) Node-strength centrality for each CAARMS symptom, and (right) stability of centrality indices. Centrality measures are shown as standardized z-scores. The right panel indicates the average correlation with the original sample after reducing the sample size through case-dropping bootstrapping. For a color version, see this figure online.
Fig. 3.
Fig. 3.
Node-specific predictive betweenness. The white dots represent the node-specific predictive betweenness in the current sample, while the black lines represent the variability of node-specific betweenness across 1,000 nonparametric bootstrap iterations.
Fig. 4.
Fig. 4.
(Left) Network showing the shortest paths between the OCS and the positive symptoms of the CAARMS scale (P1, P2, P3, and P4) and stability analyses (right). The right panel displays the extent to which the pathways were identified across 1,000 non-parametric bootstraps (eg, the 0.85 edge between GP6 and GP5 indicated the edges was identified in 85% of the cases). For a color version, see this figure online.
See this image and copyright information in PMC

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