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The whole is greater than the sum of its parts: profiles of multiple mental health risk factors using Latent class analysis
BACKGROUND: The exposure to an accumulation of various risk factors during childhood and adolescence relative to a single risk is associated with poorer mental health. Identification of distinct constellations of risk factors is an essential step towards the development of effective prevention strat...
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/PMC8204434/ https://www.ncbi.nlm.nih.gov/pubmed/34127038 http://dx.doi.org/10.1186/s13034-021-00380-8 |
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author | Göbel, Kristin Cohrdes, Caroline |
author_facet | Göbel, Kristin Cohrdes, Caroline |
author_sort | Göbel, Kristin |
collection | PubMed |
description | BACKGROUND: The exposure to an accumulation of various risk factors during childhood and adolescence relative to a single risk is associated with poorer mental health. Identification of distinct constellations of risk factors is an essential step towards the development of effective prevention strategies of mental disorders. A Latent class analysis (LCA) extracts different combinations of risk factors or subgroups and examines the association between profiles of multiple risk and mental health outcomes. METHODS: The current study used longitudinal survey data (KiGGS) of 10,853 German children, adolescents and young adults. The LCA included 27 robust risk and protective factors across multiple domains for mental health. RESULTS: The LCA identified four subgroups of individuals with different risk profiles: a basic-risk (51.4%), high-risk (23.4%), parental-risk (11.8%) and social-risk class (13.4%). Multiple risk factors of the family domain, in particular family instability were associated with negative mental health outcomes (e.g. mental health problems, depression, ADHD) and predominately comprised late adolescent girls. The social environment represented a more common risk domain for young males. CONCLUSION: The understanding of multiple risk and different risk “profiles” helps to understand and adjust targeted interventions with a focus on vulnerable groups. |
format | Online Article Text |
id | pubmed-8204434 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-82044342021-06-16 The whole is greater than the sum of its parts: profiles of multiple mental health risk factors using Latent class analysis Göbel, Kristin Cohrdes, Caroline Child Adolesc Psychiatry Ment Health Research Article BACKGROUND: The exposure to an accumulation of various risk factors during childhood and adolescence relative to a single risk is associated with poorer mental health. Identification of distinct constellations of risk factors is an essential step towards the development of effective prevention strategies of mental disorders. A Latent class analysis (LCA) extracts different combinations of risk factors or subgroups and examines the association between profiles of multiple risk and mental health outcomes. METHODS: The current study used longitudinal survey data (KiGGS) of 10,853 German children, adolescents and young adults. The LCA included 27 robust risk and protective factors across multiple domains for mental health. RESULTS: The LCA identified four subgroups of individuals with different risk profiles: a basic-risk (51.4%), high-risk (23.4%), parental-risk (11.8%) and social-risk class (13.4%). Multiple risk factors of the family domain, in particular family instability were associated with negative mental health outcomes (e.g. mental health problems, depression, ADHD) and predominately comprised late adolescent girls. The social environment represented a more common risk domain for young males. CONCLUSION: The understanding of multiple risk and different risk “profiles” helps to understand and adjust targeted interventions with a focus on vulnerable groups. BioMed Central 2021-06-14 /pmc/articles/PMC8204434/ /pubmed/34127038 http://dx.doi.org/10.1186/s13034-021-00380-8 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 Article Göbel, Kristin Cohrdes, Caroline The whole is greater than the sum of its parts: profiles of multiple mental health risk factors using Latent class analysis |
title | The whole is greater than the sum of its parts: profiles of multiple mental health risk factors using Latent class analysis |
title_full | The whole is greater than the sum of its parts: profiles of multiple mental health risk factors using Latent class analysis |
title_fullStr | The whole is greater than the sum of its parts: profiles of multiple mental health risk factors using Latent class analysis |
title_full_unstemmed | The whole is greater than the sum of its parts: profiles of multiple mental health risk factors using Latent class analysis |
title_short | The whole is greater than the sum of its parts: profiles of multiple mental health risk factors using Latent class analysis |
title_sort | whole is greater than the sum of its parts: profiles of multiple mental health risk factors using latent class analysis |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8204434/ https://www.ncbi.nlm.nih.gov/pubmed/34127038 http://dx.doi.org/10.1186/s13034-021-00380-8 |
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