| Residential College | false |
| Status | 已發表Published |
| A network model of depressive and anxiety symptoms: a statistical evaluation | |
Cai, Hong1; Chen, Meng Yi2,3; Li, Xiao Hong4; Zhang, Ling5; Su, Zhaohui6; Cheung, Teris7; Tang, Yi Lang8,9; Malgaroli, Matteo10; Jackson, Todd11; Zhang, Qinge5; Xiang, Yu Tao2,3
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| 2024-03-01 | |
| Source Publication | Molecular Psychiatry
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| ISSN | 1359-4184 |
| Volume | 29Issue:3Pages:767-781 |
| Abstract | Background: Although network analysis studies of psychiatric syndromes have increased in recent years, most have emphasized centrality symptoms and robust edges. Broadening the focus to include bridge symptoms within a systematic review could help to elucidate symptoms having the strongest links in network models of psychiatric syndromes. We conducted this systematic review and statistical evaluation of network analyses on depressive and anxiety symptoms to identify the most central symptoms and bridge symptoms, as well as the most robust edge indices of networks. Methods: A systematic literature search was performed in PubMed, PsycINFO, Web of Science, and EMBASE databases from their inception to May 25, 2022. To determine the most influential symptoms and connections, we analyzed centrality and bridge centrality rankings and aggregated the most robust symptom connections into a summary network. After determining the most central symptoms and bridge symptoms across network models, heterogeneity across studies was examined using linear logistic regression. Results: Thirty-three studies with 78,721 participants were included in this systematic review. Seventeen studies with 23 cross-sectional networks based on the Patient Health Questionnaire (PHQ) and Generalized Anxiety Disorder (GAD-7) assessments of clinical and community samples were examined using centrality scores. Twelve cross-sectional networks based on the PHQ and GAD-7 assessments were examined using bridge centrality scores. We found substantial variability between study samples and network features. ‘Sad mood’, ‘Uncontrollable worry’, and ‘Worrying too much’ were the most central symptoms, while ‘Sad mood’, ‘Restlessness’, and ‘Motor disturbance’ were the most frequent bridge centrality symptoms. In addition, the connection between ‘Sleep’ and ‘Fatigue’ was the most frequent edge for the depressive and anxiety symptoms network model. Conclusion: Central symptoms, bridge symptoms and robust edges identified in this systematic review can be viewed as potential intervention targets. We also identified gaps in the literature and future directions for network analysis of comorbid depression and anxiety. |
| DOI | 10.1038/s41380-023-02369-5 |
| URL | View the original |
| Language | 英語English |
| Scopus ID | 2-s2.0-85182852041 |
| Fulltext Access | |
| Citation statistics | |
| Document Type | Journal article |
| Collection | DEPARTMENT OF PUBLIC HEALTH AND MEDICINAL ADMINISTRATION |
| Affiliation | 1.Unit of medical psychology and behavior medicine, school of public health, Guangxi Medical University, Nanning, Guangxi, China 2.Unit of Psychiatry, Department of Public Health and Medicinal Administration, & Institute of Translational Medicine, Faculty of Health Sciences, University of Macau, Macao 3.Centre for Cognitive and Brain Sciences, University of Macau, SAR, Macao 4.Beijing Huilongguan Hospital, Peking University Huilongguan Clinical Medical School, Beijing, China 5.Beijing Key Laboratory of Mental Disorders, National Clinical Research Center for Mental Disorders & National Center for Mental Disorders, Beijing Anding Hospital; Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China 6.School of Public Health, Southeast University, Nanjing, China 7.School of Nursing, Hong Kong Polytechnic University, Hong Kong 8.Department of Psychiatry and Behavioral Sciences, Emory University, Atlanta, United States 9.Atlanta VA Medical Center, Atlanta, United States 10.Department of Psychiatry, NYU Grossman School of Medicine, New York, United States 11.Department of Psychology, University of Macau, Macao |
| Recommended Citation GB/T 7714 | Cai, Hong,Chen, Meng Yi,Li, Xiao Hong,et al. A network model of depressive and anxiety symptoms: a statistical evaluation[J]. Molecular Psychiatry, 2024, 29(3), 767-781. |
| APA | Cai, Hong., Chen, Meng Yi., Li, Xiao Hong., Zhang, Ling., Su, Zhaohui., Cheung, Teris., Tang, Yi Lang., Malgaroli, Matteo., Jackson, Todd., Zhang, Qinge., & Xiang, Yu Tao (2024). A network model of depressive and anxiety symptoms: a statistical evaluation. Molecular Psychiatry, 29(3), 767-781. |
| MLA | Cai, Hong,et al."A network model of depressive and anxiety symptoms: a statistical evaluation".Molecular Psychiatry 29.3(2024):767-781. |
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