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Latent profile analysis of anxiety disorder among left-behind children in rural Southern China: a cross-sectional study
OBJECTIVES: Previous studies have used latent profile analysis (LPA) to examine rural left-behind children’s anxiety. Further study is needed to identify the heterogeneous characteristics of rural left-behind children’s anxiety and explore the related factors. SETTING: A cross-sectional survey using...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BMJ Publishing Group
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6589011/ https://www.ncbi.nlm.nih.gov/pubmed/31221893 http://dx.doi.org/10.1136/bmjopen-2019-029331 |
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author | Liao, Haining Pan, Minyi Li, Weinan Lin, Changqi Zhu, Xuhao Li, Xingru Li, Jinghua Zhou, Shudong |
author_facet | Liao, Haining Pan, Minyi Li, Weinan Lin, Changqi Zhu, Xuhao Li, Xingru Li, Jinghua Zhou, Shudong |
author_sort | Liao, Haining |
collection | PubMed |
description | OBJECTIVES: Previous studies have used latent profile analysis (LPA) to examine rural left-behind children’s anxiety. Further study is needed to identify the heterogeneous characteristics of rural left-behind children’s anxiety and explore the related factors. SETTING: A cross-sectional survey using a school-based sample was conducted in January 2018 in Qingxin district, Qingyuan city, Guangdong province. PARTICIPANTS: 1026 left-behind children (effective response rate of the questionnaire: 95.39%). MAIN OUTCOME MEASURES: Profile latent classes (LC) and anxiety disorder. RESULTS: The LPA identified three anxiety LC: ‘low anxiety’ (56.6%), ‘medium anxiety’ (34.8%) and ‘severe anxiety’ (8.6%). The multinomial logistic regression model was used to predict the relationship between personal, family, school factors and anxiety. We found that the variables directly related to lower anxiety classes included age (12–14 years), harmonious or fair relationship with classmates, no neglect, harmonious parental relationship and the duration of mother migration <6 months. CONCLUSIONS: These findings suggested the need for careful consideration of differences in anxieties among rural left-behind children. Identifying latent subgroups may provide an empirical basis for teachers and public health practitioners to implement anxiety intervention efforts. |
format | Online Article Text |
id | pubmed-6589011 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | BMJ Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-65890112019-07-05 Latent profile analysis of anxiety disorder among left-behind children in rural Southern China: a cross-sectional study Liao, Haining Pan, Minyi Li, Weinan Lin, Changqi Zhu, Xuhao Li, Xingru Li, Jinghua Zhou, Shudong BMJ Open Mental Health OBJECTIVES: Previous studies have used latent profile analysis (LPA) to examine rural left-behind children’s anxiety. Further study is needed to identify the heterogeneous characteristics of rural left-behind children’s anxiety and explore the related factors. SETTING: A cross-sectional survey using a school-based sample was conducted in January 2018 in Qingxin district, Qingyuan city, Guangdong province. PARTICIPANTS: 1026 left-behind children (effective response rate of the questionnaire: 95.39%). MAIN OUTCOME MEASURES: Profile latent classes (LC) and anxiety disorder. RESULTS: The LPA identified three anxiety LC: ‘low anxiety’ (56.6%), ‘medium anxiety’ (34.8%) and ‘severe anxiety’ (8.6%). The multinomial logistic regression model was used to predict the relationship between personal, family, school factors and anxiety. We found that the variables directly related to lower anxiety classes included age (12–14 years), harmonious or fair relationship with classmates, no neglect, harmonious parental relationship and the duration of mother migration <6 months. CONCLUSIONS: These findings suggested the need for careful consideration of differences in anxieties among rural left-behind children. Identifying latent subgroups may provide an empirical basis for teachers and public health practitioners to implement anxiety intervention efforts. BMJ Publishing Group 2019-06-19 /pmc/articles/PMC6589011/ /pubmed/31221893 http://dx.doi.org/10.1136/bmjopen-2019-029331 Text en © Author(s) (or their employer(s)) 2019. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ. This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/. |
spellingShingle | Mental Health Liao, Haining Pan, Minyi Li, Weinan Lin, Changqi Zhu, Xuhao Li, Xingru Li, Jinghua Zhou, Shudong Latent profile analysis of anxiety disorder among left-behind children in rural Southern China: a cross-sectional study |
title | Latent profile analysis of anxiety disorder among left-behind children in rural Southern China: a cross-sectional study |
title_full | Latent profile analysis of anxiety disorder among left-behind children in rural Southern China: a cross-sectional study |
title_fullStr | Latent profile analysis of anxiety disorder among left-behind children in rural Southern China: a cross-sectional study |
title_full_unstemmed | Latent profile analysis of anxiety disorder among left-behind children in rural Southern China: a cross-sectional study |
title_short | Latent profile analysis of anxiety disorder among left-behind children in rural Southern China: a cross-sectional study |
title_sort | latent profile analysis of anxiety disorder among left-behind children in rural southern china: a cross-sectional study |
topic | Mental Health |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6589011/ https://www.ncbi.nlm.nih.gov/pubmed/31221893 http://dx.doi.org/10.1136/bmjopen-2019-029331 |
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