ArticleFrontiers in psychiatry2026
Mapping the network structure of anxiety, depression, and sleep symptoms in patients with polycystic ovary syndrome.
Article in Frontiers in psychiatry, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Background: Patients with polycystic ovary syndrome (PCOS) often experience anxiety, depression, and sleep problems in addition to endocrine and metabolic abnormalities, which may adversely affect their quality of life and disease progression. However, research on the co-occurrence patterns and interconnections among these psychological symptoms in PCOS remains limited. This study applied network analysis to explore the relationships among anxiety, depression, and sleep problems in women with PCOS, aiming to identify key symptom nodes and provide evidence for targeted psychological interventions. Methods: This retrospective study included 1,068 patients with PCOS. Anxiety, depression, and sleep problems were assessed using the Generalized Anxiety Disorder Scale (GAD-7), Patient Health Questionnaire (PHQ-9), and Pittsburgh Sleep Quality Index (PSQI). Symptom networks were estimated using the Least Absolute Shrinkage and Selection Operator (LASSO) and Extended Bayesian Information Criterion (EBIC) in R software. Central and bridge symptoms were identified using expected influence (EI) and bridge expected influence (BEI). Network stability and accuracy were evaluated through bootstrap methods. The Network Comparison Test (NCT) was applied to analyze network differences across subgroups that vary by marital status and weight status. Results: Network analysis revealed that the strongest edge was the connection between "Daytime dysfunction" and "Low energy" (PSQI7-PHQ4), spanning different symptom communities. Another edge of high intensity was observed between "Worthlessness" and "Suicidal ideation" (PHQ6-PHQ9). "Trouble relaxing" (GAD4) and "Sad mood" (PHQ2) exhibited the highest EI values within the network. Meanwhile, "Daytime dysfunction" (PSQI7) and "Low energy" (PHQ4) showed the highest BEI values. Network comparison analysis revealed no significant differences across marital and weight status subgroups. Conclusion: This study is the first to explore the symptom interrelationships among anxiety, depression, and sleep problems in PCOS patients. Targeting these central symptoms (e.g., trouble relaxing, sad mood) and bridging symptoms (e.g., daytime dysfunction, low energy) may more effectively alleviate patients' overall psychological issues and potentially interrupt the spread of comorbid psychiatric conditions. The findings of this study can inform the development of personalized mental health management strategies for patients with PCOS.
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