Psychiatry research · 2026
Biopsychosocial correlates of active suicidal ideation in obsessive-compulsive disorder.
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Huang Xinqi, Kuang Xiaolong
Аннотация
BACKGROUND: Active suicidal ideation (ASI) in patients with obsessive-compulsive disorder (OCD) is a clinically important but understudied phenomenon. Prior research has focused largely on symptom severity and comorbid depression, overlooking potential hormonal and psychosocial influences. This study aimed to identify biopsychosocial correlates of ASI in OCD using an integrative analytic framework.
METHODS: A total of 114 hospitalized patients with OCD were assessed for active ASI, clinical symptoms, hormone levels, and psychosocial factors. Univariate analyses were conducted using appropriate statistical tests. A Spearman-based network analysis was used to map inter-variable connectivity and identify central nodes. Multivariable logistic regression was performed to identify independent predictors, with sensitivity analyses using 1:1 age- and sex-matched subsamples to assess model robustness.
RESULTS: ASI was reported by 33.3% of participants. Univariate and stratified analyses revealed significantly higher estradiol (E2) levels in individuals with ASI, especially among males. Network analysis showed that ASI was directly connected to anxiety severity, E2, insight, and economic status. E2 demonstrated the highest centrality in the network. Multivariable modeling identified anxiety severity (OR = 2.77, p = 0.001), insight (OR = 3.16, p = 0.036), and E2 (OR = 1.68, p = 0.061) as key predictors. The model achieved an AUC of 0.769, which increased to 0.857 in matched sensitivity analysis.
CONCLUSIONS: ASI in OCD arises from interconnected affective, cognitive, and biological mechanisms. Incorporating hormonal and self-perceptual factors into suicide risk evaluation may improve risk evaluation, with E2 identified as a potential biomarker, especially among males.
METHODS: A total of 114 hospitalized patients with OCD were assessed for active ASI, clinical symptoms, hormone levels, and psychosocial factors. Univariate analyses were conducted using appropriate statistical tests. A Spearman-based network analysis was used to map inter-variable connectivity and identify central nodes. Multivariable logistic regression was performed to identify independent predictors, with sensitivity analyses using 1:1 age- and sex-matched subsamples to assess model robustness.
RESULTS: ASI was reported by 33.3% of participants. Univariate and stratified analyses revealed significantly higher estradiol (E2) levels in individuals with ASI, especially among males. Network analysis showed that ASI was directly connected to anxiety severity, E2, insight, and economic status. E2 demonstrated the highest centrality in the network. Multivariable modeling identified anxiety severity (OR = 2.77, p = 0.001), insight (OR = 3.16, p = 0.036), and E2 (OR = 1.68, p = 0.061) as key predictors. The model achieved an AUC of 0.769, which increased to 0.857 in matched sensitivity analysis.
CONCLUSIONS: ASI in OCD arises from interconnected affective, cognitive, and biological mechanisms. Incorporating hormonal and self-perceptual factors into suicide risk evaluation may improve risk evaluation, with E2 identified as a potential biomarker, especially among males.