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...
| Main Authors: | , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2023-10-01
|
| Series: | Behavioral Sciences |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2076-328X/13/11/893 |
| _version_ | 1797460209891803136 |
|---|---|
| author | Chen Wang Ting Zhou Lin Fu Dong Xie Huiying Qi Zheng Huang |
| author_facet | Chen Wang Ting Zhou Lin Fu Dong Xie Huiying Qi Zheng Huang |
| author_sort | Chen Wang |
| collection | DOAJ |
| 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. |
| first_indexed | 2024-03-09T17:01:54Z |
| format | Article |
| id | doaj.art-c193051247b5454d97ed0b34929f6507 |
| institution | Directory Open Access Journal |
| issn | 2076-328X |
| language | English |
| last_indexed | 2024-03-09T17:01:54Z |
| publishDate | 2023-10-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Behavioral Sciences |
| spelling | doaj.art-c193051247b5454d97ed0b34929f65072023-11-24T14:29:18ZengMDPI AGBehavioral Sciences2076-328X2023-10-01131189310.3390/bs13110893Risk and Protective Factors of Depression in Family and School Domains for Chinese Early Adolescents: An Association Rule Mining ApproachChen Wang0Ting Zhou1Lin Fu2Dong Xie3Huiying Qi4Zheng Huang5Department of Health Informatics and Management, School of Health Humanities, Peking University, Beijing 100191, ChinaDepartment of Medical Psychology, School of Health Humanities, Peking University, Beijing 100191, ChinaFaculty of Humanities and Social Sciences, Beijing University of Technology, Beijing 100124, ChinaSchool of Basic Medical Sciences, Peking University, Beijing 100191, ChinaDepartment of Health Informatics and Management, School of Health Humanities, Peking University, Beijing 100191, ChinaDepartment of Psychology, University of Chinese Academy of Sciences, Beijing 100101, ChinaDepression 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.https://www.mdpi.com/2076-328X/13/11/893adolescent depressionage groupassociation rule mininggenderleft-behind statusprotective factors |
| spellingShingle | Chen Wang Ting Zhou Lin Fu Dong Xie Huiying Qi Zheng Huang Risk and Protective Factors of Depression in Family and School Domains for Chinese Early Adolescents: An Association Rule Mining Approach Behavioral Sciences adolescent depression age group association rule mining gender left-behind status protective factors |
| 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 | adolescent depression age group association rule mining gender left-behind status protective factors |
| url | https://www.mdpi.com/2076-328X/13/11/893 |
| work_keys_str_mv | AT chenwang riskandprotectivefactorsofdepressioninfamilyandschooldomainsforchineseearlyadolescentsanassociationruleminingapproach AT tingzhou riskandprotectivefactorsofdepressioninfamilyandschooldomainsforchineseearlyadolescentsanassociationruleminingapproach AT linfu riskandprotectivefactorsofdepressioninfamilyandschooldomainsforchineseearlyadolescentsanassociationruleminingapproach AT dongxie riskandprotectivefactorsofdepressioninfamilyandschooldomainsforchineseearlyadolescentsanassociationruleminingapproach AT huiyingqi riskandprotectivefactorsofdepressioninfamilyandschooldomainsforchineseearlyadolescentsanassociationruleminingapproach AT zhenghuang riskandprotectivefactorsofdepressioninfamilyandschooldomainsforchineseearlyadolescentsanassociationruleminingapproach |