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A Network Model of Resilience Factors for Adolescents with and without Exposure to Childhood Adversity
Resilience factors (RFs) help prevent mental health problems after childhood adversity (CA). RFs are known to be related, but it is currently unknown how their interrelations facilitate mental health. Here, we used network analysis to examine the interrelations between ten RFs in 14-year-old adolesc...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6202387/ https://www.ncbi.nlm.nih.gov/pubmed/30361515 http://dx.doi.org/10.1038/s41598-018-34130-2 |
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author | Fritz, J. Fried, E. I. Goodyer, I. M. Wilkinson, P. O. van Harmelen, A.-L. |
author_facet | Fritz, J. Fried, E. I. Goodyer, I. M. Wilkinson, P. O. van Harmelen, A.-L. |
author_sort | Fritz, J. |
collection | PubMed |
description | Resilience factors (RFs) help prevent mental health problems after childhood adversity (CA). RFs are known to be related, but it is currently unknown how their interrelations facilitate mental health. Here, we used network analysis to examine the interrelations between ten RFs in 14-year-old adolescents exposed (‘CA’; n = 638) and not exposed to CA (‘no-CA’; n = 501). We found that the degree to which RFs are assumed to enhance each other is higher in the no-CA compared to the CA group. Upon correction for general distress levels, the global RF connectivity also differed between the two groups. More specifically, in the no-CA network almost all RFs were positively interrelated and thus may enhance each other, whereas in the CA network some RFs were negatively interrelated and thus may hamper each other. Moreover, the CA group showed more direct connections between the RFs and current distress. Therefore, CA seems to influence how RFs relate to each other and to current distress, potentially leading to a dysfunctional RF system. Translational research could explore whether intervening on negative RF interrelations so that they turn positive and RFs can enhance each other, may alter ‘RF-mental distress’ relations, resulting in a lower risk for subsequent mental health problems. |
format | Online Article Text |
id | pubmed-6202387 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-62023872018-10-29 A Network Model of Resilience Factors for Adolescents with and without Exposure to Childhood Adversity Fritz, J. Fried, E. I. Goodyer, I. M. Wilkinson, P. O. van Harmelen, A.-L. Sci Rep Article Resilience factors (RFs) help prevent mental health problems after childhood adversity (CA). RFs are known to be related, but it is currently unknown how their interrelations facilitate mental health. Here, we used network analysis to examine the interrelations between ten RFs in 14-year-old adolescents exposed (‘CA’; n = 638) and not exposed to CA (‘no-CA’; n = 501). We found that the degree to which RFs are assumed to enhance each other is higher in the no-CA compared to the CA group. Upon correction for general distress levels, the global RF connectivity also differed between the two groups. More specifically, in the no-CA network almost all RFs were positively interrelated and thus may enhance each other, whereas in the CA network some RFs were negatively interrelated and thus may hamper each other. Moreover, the CA group showed more direct connections between the RFs and current distress. Therefore, CA seems to influence how RFs relate to each other and to current distress, potentially leading to a dysfunctional RF system. Translational research could explore whether intervening on negative RF interrelations so that they turn positive and RFs can enhance each other, may alter ‘RF-mental distress’ relations, resulting in a lower risk for subsequent mental health problems. Nature Publishing Group UK 2018-10-25 /pmc/articles/PMC6202387/ /pubmed/30361515 http://dx.doi.org/10.1038/s41598-018-34130-2 Text en © The Author(s) 2018 Open Access This 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 license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license 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 license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Fritz, J. Fried, E. I. Goodyer, I. M. Wilkinson, P. O. van Harmelen, A.-L. A Network Model of Resilience Factors for Adolescents with and without Exposure to Childhood Adversity |
title | A Network Model of Resilience Factors for Adolescents with and without Exposure to Childhood Adversity |
title_full | A Network Model of Resilience Factors for Adolescents with and without Exposure to Childhood Adversity |
title_fullStr | A Network Model of Resilience Factors for Adolescents with and without Exposure to Childhood Adversity |
title_full_unstemmed | A Network Model of Resilience Factors for Adolescents with and without Exposure to Childhood Adversity |
title_short | A Network Model of Resilience Factors for Adolescents with and without Exposure to Childhood Adversity |
title_sort | network model of resilience factors for adolescents with and without exposure to childhood adversity |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6202387/ https://www.ncbi.nlm.nih.gov/pubmed/30361515 http://dx.doi.org/10.1038/s41598-018-34130-2 |
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