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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 |
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author | Li, Kuiliang Guang, Yu Ren, Lei Zhan, Xiaoqing Tan, Xuejiao Luo, Xi Feng, Zhengzhi |
author_facet | Li, Kuiliang Guang, Yu Ren, Lei Zhan, Xiaoqing Tan, Xuejiao Luo, Xi Feng, Zhengzhi |
author_sort | Li, Kuiliang |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-8408940 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-84089402021-09-01 Network analysis of the relationship between negative life events and depressive symptoms in the left-behind children Li, Kuiliang Guang, Yu Ren, Lei Zhan, Xiaoqing Tan, Xuejiao Luo, Xi Feng, Zhengzhi BMC Psychiatry Research 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. BioMed Central 2021-09-01 /pmc/articles/PMC8408940/ /pubmed/34470646 http://dx.doi.org/10.1186/s12888-021-03445-2 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Li, Kuiliang Guang, Yu Ren, Lei Zhan, Xiaoqing Tan, Xuejiao Luo, Xi Feng, Zhengzhi Network analysis of the relationship between negative life events and depressive symptoms in the left-behind children |
title | Network analysis of the relationship between negative life events and depressive symptoms in the left-behind children |
title_full | Network analysis of the relationship between negative life events and depressive symptoms in the left-behind children |
title_fullStr | Network analysis of the relationship between negative life events and depressive symptoms in the left-behind children |
title_full_unstemmed | Network analysis of the relationship between negative life events and depressive symptoms in the left-behind children |
title_short | Network analysis of the relationship between negative life events and depressive symptoms in the left-behind children |
title_sort | network analysis of the relationship between negative life events and depressive symptoms in the left-behind children |
topic | Research |
url | 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 |
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