ORIGINAL RESEARCH article
Front. Psychiatry
Sec. Computational Psychiatry
1. Anhui Medical University, Hefei, China
2. Zhejiang University School of Medicine Affiliated Mental Health Centre & Hangzhou Seventh People’s Hospital, Hangzhou, China
3. Chaohu Hospital of Anhui Medical University, Hefei, China
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Abstract
Background: The co-occurrence of obsessive-compulsive disorder (OCD) and psychotic-like symptoms suggests the existence of the “obsessive-schizophrenic spectrum”, and this study uses network analysis to explore their interaction mechanism. Methods: A total of 528 patients with obsessive-compulsive disorder (OCD) were included. A symptom network was constructed based on the Yale-Brown Obsessive-Compulsive Scale (Y-BOCS), Symptom Checklist-90 (SCL-90), Self-Rating Anxiety Scale (SAS), and Self-Rating Depression Scale (SDS). Core nodes were identified through centrality indicators. Results: “Brain not right” (SCL90) has the highest betweenness centrality and serves as a crucial metacognitive mediator connecting symptom clusters. Lonely in crowd (SCL77) has the highest strength, maintaining network activation. unusual thoughts (SCL68) and Somatic concern (SCL87) emerged as a bridge node linking obsessive-compulsive symptoms to subjective experiential and thought-perceptual disturbances associated with the psychosis spectrum. Malignant loops such as “obsessive interference – collapse of metacognitive evaluation” have been identified. Conclusions: The catastrophe of brain functions and the sense of loneliness are the central hubs which drive the complexity of OCD symptoms. In addition to traditional treatments, correcting metacognitive beliefs and improving social isolation are crucial for preventing the deterioration of disease.
Summary
Keywords
Loneliness, metacognition, Network analysis, Obsessive-Compulsive Disorder, Obsessive-schizophrenic spectrum
Received
05 March 2026
Accepted
24 April 2026
Copyright
© 2026 Xu, Wu, Zhang, Liu and Zhu. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Correspondence: Huanzhong Liu; Shuangyue Zhu
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