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Network analysis of the relationship between negative life events and depressive symptoms in the left-behind children
BACKGROUND: There are 68.77 million left-behind children in China, who are at a great risk of depression associated with negative life events. Our study aims to investigate the most central symptoms of depression in left-behind children and the relationship between depressive symptoms and negative l...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8408940/ https://www.ncbi.nlm.nih.gov/pubmed/34470646 http://dx.doi.org/10.1186/s12888-021-03445-2 |
Sumario: | BACKGROUND: There are 68.77 million left-behind children in China, who are at a great risk of depression associated with negative life events. Our study aims to investigate the most central symptoms of depression in left-behind children and the relationship between depressive symptoms and negative life events using network analysis. METHOD: A cross-sectional data set (N = 7255) was used, which included children and adolescents aged 7 to 17. Network analysis was used to evaluate: 1) the most central symptoms among the items included in Child Depression Inventory (CDI) of the left-behind children; 2) bridge symptoms between depressive disorder and Adolescent Self-Rating Life Events Check List (ASLEC) of the left-behind children; 3) differences in networks of depressive disorders between left-behind and non-left-behind children, and 4) differences in the network of depression and negative life events between left-behind and non-left-behind children. The stability and centrality indices of the network were also evaluated in the study. RESULTS: The most central symptoms in the CDI among the left-behind children included self-hatred, crying, fatigue, and sadness. The items with the highest bridge strength centrality in the CDI-ASLEC network included academic stress, discrimination, and school performance decrement. Higher bridge strength values indicate a greater risk of contagion to other communities. The connections in the CDI-ASLEC network are denser in the left-behind children than in non-left-behind children. LIMITATIONS: The study which was conducted based on cross-sectional data shows that network analysis can only make undirected estimation, but not causal inferences. CONCLUSIONS: We identified the core symptoms of depression and the bridge symptoms between negative life events and depression in the left-behind children. These findings suggest that more attention should be paid to self-hatred, sadness, and fatigue in the treatment of depression in left-behind children. Intervention for academic stress and discrimination of the left-behind children may help to reduce the contagion of negative life events to depression symptoms. |
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