Cargando…
Risk and Protective Factors of Depression in Family and School Domains for Chinese Early Adolescents: An Association Rule Mining Approach
Depression is one of the most common psychological problems in adolescence. Familial and school-related factors are closely related to adolescents’ depression, but their combined effects need further examination. The purpose of this study was to explore the combined effects of risk/protective factor...
Autores principales: | , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10669531/ https://www.ncbi.nlm.nih.gov/pubmed/37998640 http://dx.doi.org/10.3390/bs13110893 |
_version_ | 1785139718865813504 |
---|---|
author | Wang, Chen Zhou, Ting Fu, Lin Xie, Dong Qi, Huiying Huang, Zheng |
author_facet | Wang, Chen Zhou, Ting Fu, Lin Xie, Dong Qi, Huiying Huang, Zheng |
author_sort | Wang, Chen |
collection | PubMed |
description | Depression is one of the most common psychological problems in adolescence. Familial and school-related factors are closely related to adolescents’ depression, but their combined effects need further examination. The purpose of this study was to explore the combined effects of risk/protective factors of depression in family and school domains using a sample of Chinese adolescents differing in gender, age group and left-behind status. A total of 2455 Chinese students in primary and secondary school participated in the cross-sectional survey and reported multiple risk/protective factors in family and school environments and depressive symptoms. Association rule mining, a machine learning method, was used in the data analyses to identify the correlation between risk/protective factor combinations and depression. We found that (1) Family cohesion, family conflict, peer support, and teacher support emerged as the strongest factors associated with adolescent depression; (2) The combination of these aforementioned factors further strengthened their association with depression; (3) Female gender, middle school students, and family socioeconomic disadvantages attenuated the protective effects of positive relational factors while exacerbating the deleterious effects of negative relational factors; (4) For individuals at risk, lack of mental health education resources at school intensified the negative impact; (5) The risk and protective factors of depression varied according to gender, age stage and left-behind status. In conclusion, the findings shed light on the identification of high-risk adolescents for depression and underscore the importance of tailored programs targeting specific subgroups based on gender, age, or left-behind status. |
format | Online Article Text |
id | pubmed-10669531 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-106695312023-10-29 Risk and Protective Factors of Depression in Family and School Domains for Chinese Early Adolescents: An Association Rule Mining Approach Wang, Chen Zhou, Ting Fu, Lin Xie, Dong Qi, Huiying Huang, Zheng Behav Sci (Basel) Article Depression is one of the most common psychological problems in adolescence. Familial and school-related factors are closely related to adolescents’ depression, but their combined effects need further examination. The purpose of this study was to explore the combined effects of risk/protective factors of depression in family and school domains using a sample of Chinese adolescents differing in gender, age group and left-behind status. A total of 2455 Chinese students in primary and secondary school participated in the cross-sectional survey and reported multiple risk/protective factors in family and school environments and depressive symptoms. Association rule mining, a machine learning method, was used in the data analyses to identify the correlation between risk/protective factor combinations and depression. We found that (1) Family cohesion, family conflict, peer support, and teacher support emerged as the strongest factors associated with adolescent depression; (2) The combination of these aforementioned factors further strengthened their association with depression; (3) Female gender, middle school students, and family socioeconomic disadvantages attenuated the protective effects of positive relational factors while exacerbating the deleterious effects of negative relational factors; (4) For individuals at risk, lack of mental health education resources at school intensified the negative impact; (5) The risk and protective factors of depression varied according to gender, age stage and left-behind status. In conclusion, the findings shed light on the identification of high-risk adolescents for depression and underscore the importance of tailored programs targeting specific subgroups based on gender, age, or left-behind status. MDPI 2023-10-29 /pmc/articles/PMC10669531/ /pubmed/37998640 http://dx.doi.org/10.3390/bs13110893 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Wang, Chen Zhou, Ting Fu, Lin Xie, Dong Qi, Huiying Huang, Zheng Risk and Protective Factors of Depression in Family and School Domains for Chinese Early Adolescents: An Association Rule Mining Approach |
title | Risk and Protective Factors of Depression in Family and School Domains for Chinese Early Adolescents: An Association Rule Mining Approach |
title_full | Risk and Protective Factors of Depression in Family and School Domains for Chinese Early Adolescents: An Association Rule Mining Approach |
title_fullStr | Risk and Protective Factors of Depression in Family and School Domains for Chinese Early Adolescents: An Association Rule Mining Approach |
title_full_unstemmed | Risk and Protective Factors of Depression in Family and School Domains for Chinese Early Adolescents: An Association Rule Mining Approach |
title_short | Risk and Protective Factors of Depression in Family and School Domains for Chinese Early Adolescents: An Association Rule Mining Approach |
title_sort | risk and protective factors of depression in family and school domains for chinese early adolescents: an association rule mining approach |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10669531/ https://www.ncbi.nlm.nih.gov/pubmed/37998640 http://dx.doi.org/10.3390/bs13110893 |
work_keys_str_mv | AT wangchen riskandprotectivefactorsofdepressioninfamilyandschooldomainsforchineseearlyadolescentsanassociationruleminingapproach AT zhouting riskandprotectivefactorsofdepressioninfamilyandschooldomainsforchineseearlyadolescentsanassociationruleminingapproach AT fulin riskandprotectivefactorsofdepressioninfamilyandschooldomainsforchineseearlyadolescentsanassociationruleminingapproach AT xiedong riskandprotectivefactorsofdepressioninfamilyandschooldomainsforchineseearlyadolescentsanassociationruleminingapproach AT qihuiying riskandprotectivefactorsofdepressioninfamilyandschooldomainsforchineseearlyadolescentsanassociationruleminingapproach AT huangzheng riskandprotectivefactorsofdepressioninfamilyandschooldomainsforchineseearlyadolescentsanassociationruleminingapproach |