A national survey of suicidality and non-suicidal self-injury in bipolar disorder: insights from network analysis

作者：Lvchun Cui, Yuncheng Zhu, Yang Li, Jia Zhou, Guiyun Xu, Pan Miao, Zhiyu Chen, Wenfei Li, Zhian Jiao, Mingli Li, Yong Zhang, Jingxu Chen, Xiuzhe Chen, Na Li, Jing Sun, Jian Zhang, Shaohua Hu, Haishan Wu, Zhaoyu Gan, Yan Qin, Yumei Wang, Yantao Ma, Xiaoping Wang, Xiaohong Li, Chuangxin Wu, Yiyun Cai, Jiaye Chen, Baichuan Wu, Zuowei Wang, Daihui Peng, Yi-Ru Fang · 发表于：BMC Psychiatry · 年份：2025 · DOI：10.1186/s12888-025-06750-2 · 被引用次数：7 · 研究领域：Bipolar Disorder and Treatment、Mental Health Research Topics、Suicide and Self-Harm Studies

BACKGROUND: There is a high prevalence of suicidal ideation (SI), suicide attempts (SA), and non-suicidal self-injury (NSSI) in bipolar disorder (BD). Understanding the nature of suicidality and NSSI in BD is an important way to inform optimal intervention for reducing suicide risk. We aimed to investigate the prevalence and correlates of SI, SA, and NSSI in patients with BD using data from a national survey. We used network analysis to explore the associations among suicidality, NSSI, addictive features of NSSI, and symptoms of BD. METHODS: Participants with BD were recruited from 20 research centers in China. Suicidality, NSSI, addictive features, and symptoms of BD were measured via a standardized electronic case report form. We used logistic regression and network analysis for data analysis. RESULTS: Of the 1,055 participants recruited, over 50% with depressive or mixed episodes had SI, more than 20% engaged in SA, and over 40% reported NSSI. The polarity of mood episodes was independently associated with SI ([hypo]mania vs. mixed episodes: odds ratio [OR] = 0.22, 95% confidence interval [CI] 0.14-0.33, p < 0.001) and NSSI ([hypo]mania vs. mixed episodes: OR = 0.33, 95% CI 0.19-0.58, p < 0.001; depressive episodes vs. mixed episodes: OR = 0.59, 95% CI 0.35-0.98, p = 0.040). Participants with mixed episodes reported the most severe addictive features of NSSI. SI was the most influential symptom within the network model of the total sample; NSSI, SI, and depressive symptoms...