The relationship between anxiety and depression symptoms in insomnia patients: a network analysis
Abstract Anxiety and depressive symptoms are both common in insomnia patients, and they share a critical bidirectional relationship. The available research suggests that transitioning from a disorder-level analysis to a symptom-level analysis may provide a clearer understanding of these relationship...
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Nature Portfolio
2025-07-01
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| Series: | Scientific Reports |
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| Online Access: | https://doi.org/10.1038/s41598-025-09746-w |
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| author | Yu Liu Zirong Zhu Jiaran Yan Yuanyuan Wang |
| author_facet | Yu Liu Zirong Zhu Jiaran Yan Yuanyuan Wang |
| author_sort | Yu Liu |
| collection | DOAJ |
| description | Abstract Anxiety and depressive symptoms are both common in insomnia patients, and they share a critical bidirectional relationship. The available research suggests that transitioning from a disorder-level analysis to a symptom-level analysis may provide a clearer understanding of these relationships. A total of 1571 insomnia patients were enrolled in this study. Sleep quality was assessed using the Pittsburgh Sleep Quality Index (PSQI), anxiety symptoms were evaluated using the Hamilton Rating Scale for Anxiety (HAM-A), and depressive symptoms were evaluated using the Hamilton Rating Scale for Depression (HAM-D). Subsequently, a network analysis was conducted for the statistical analysis. Among the present sample, the prevalences of depression and anxiety were 87.1% and 88.0%, respectively. We found that the strongest regularized partial correlations existed in the network between “C3: Sleep duration” and “C4: Habitual sleep efficiency” (r = 0.91). Two other strong regularized partial correlations were observed between “B3: Cognitive disturbance” - “B7: Hopelessness” (r = 0.36), “A2: Psychic anxiety” - “B5: Retardation” (r = 0.28). In addition, the item “C3: Sleep duration” had the highest strength centrality in the network, followed by “C1: Subjective sleep quality”, “C4: Habitual sleep efficiency”, “A2: Psychic anxiety”, “B1: Anxiety/Somatization”. The findings highlight the crucial role of the strongest regularized partial correlations and bridge symptoms in relation to depression and anxiety. Targeted interventions for clinical control of anxiety and depressive symptoms in insomnia patients are promising. |
| format | Article |
| id | doaj-art-c15e4ce3befa4ff3bf630b586f1eebf1 |
| institution | DOAJ |
| issn | 2045-2322 |
| language | English |
| publishDate | 2025-07-01 |
| publisher | Nature Portfolio |
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| spelling | doaj-art-c15e4ce3befa4ff3bf630b586f1eebf12025-08-20T03:04:25ZengNature PortfolioScientific Reports2045-23222025-07-0115111010.1038/s41598-025-09746-wThe relationship between anxiety and depression symptoms in insomnia patients: a network analysisYu Liu0Zirong Zhu1Jiaran Yan2Yuanyuan Wang3Department of Neurology, The Air Force Hospital of Northern Theater PLADepartment of Neurology, Xijing Hospital, Fourth Military Medical UniversityDepartment of Nursing, The Air Force Hospital of Northern Theater PLADepartment of Neurology, The Air Force Hospital of Northern Theater PLAAbstract Anxiety and depressive symptoms are both common in insomnia patients, and they share a critical bidirectional relationship. The available research suggests that transitioning from a disorder-level analysis to a symptom-level analysis may provide a clearer understanding of these relationships. A total of 1571 insomnia patients were enrolled in this study. Sleep quality was assessed using the Pittsburgh Sleep Quality Index (PSQI), anxiety symptoms were evaluated using the Hamilton Rating Scale for Anxiety (HAM-A), and depressive symptoms were evaluated using the Hamilton Rating Scale for Depression (HAM-D). Subsequently, a network analysis was conducted for the statistical analysis. Among the present sample, the prevalences of depression and anxiety were 87.1% and 88.0%, respectively. We found that the strongest regularized partial correlations existed in the network between “C3: Sleep duration” and “C4: Habitual sleep efficiency” (r = 0.91). Two other strong regularized partial correlations were observed between “B3: Cognitive disturbance” - “B7: Hopelessness” (r = 0.36), “A2: Psychic anxiety” - “B5: Retardation” (r = 0.28). In addition, the item “C3: Sleep duration” had the highest strength centrality in the network, followed by “C1: Subjective sleep quality”, “C4: Habitual sleep efficiency”, “A2: Psychic anxiety”, “B1: Anxiety/Somatization”. The findings highlight the crucial role of the strongest regularized partial correlations and bridge symptoms in relation to depression and anxiety. Targeted interventions for clinical control of anxiety and depressive symptoms in insomnia patients are promising.https://doi.org/10.1038/s41598-025-09746-wNetwork analysisInsomniaAnxietyDepressionBridge symptoms |
| spellingShingle | Yu Liu Zirong Zhu Jiaran Yan Yuanyuan Wang The relationship between anxiety and depression symptoms in insomnia patients: a network analysis Scientific Reports Network analysis Insomnia Anxiety Depression Bridge symptoms |
| title | The relationship between anxiety and depression symptoms in insomnia patients: a network analysis |
| title_full | The relationship between anxiety and depression symptoms in insomnia patients: a network analysis |
| title_fullStr | The relationship between anxiety and depression symptoms in insomnia patients: a network analysis |
| title_full_unstemmed | The relationship between anxiety and depression symptoms in insomnia patients: a network analysis |
| title_short | The relationship between anxiety and depression symptoms in insomnia patients: a network analysis |
| title_sort | relationship between anxiety and depression symptoms in insomnia patients a network analysis |
| topic | Network analysis Insomnia Anxiety Depression Bridge symptoms |
| url | https://doi.org/10.1038/s41598-025-09746-w |
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