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Does Personality Predict Depression and Use of an Internet-Based Intervention for Depression among Adolescents?
Background. Focus upon depression and prevention of its occurrence among adolescents is increasing. Novel ways of dealing with this serious problem have become available especially by means of internet-based prevention and treatment programs of depression and anxiety. The use of Internet-based inter...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi Publishing Corporation
2012
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3426188/ https://www.ncbi.nlm.nih.gov/pubmed/22928095 http://dx.doi.org/10.1155/2012/593068 |
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author | Vangberg, Hans Christian B. Lillevoll, Kjersti R. Waterloo, Knut Eisemann, Martin |
author_facet | Vangberg, Hans Christian B. Lillevoll, Kjersti R. Waterloo, Knut Eisemann, Martin |
author_sort | Vangberg, Hans Christian B. |
collection | PubMed |
description | Background. Focus upon depression and prevention of its occurrence among adolescents is increasing. Novel ways of dealing with this serious problem have become available especially by means of internet-based prevention and treatment programs of depression and anxiety. The use of Internet-based intervention programs among adolescents has revealed some difficulties in implementation that need to be further elucidated. The aim of this study is to investigate the association between personality and adolescent depression and the characteristics of users of an Internet-based intervention program. Method. The Junior Temperament and Character Inventory (JTCI), the General Self-Efficacy scale (GSE) and the Centre for Epidemiological Studies-Depression scale (CES-D) have been administered to a sample (n = 1234) of Norwegian senior high-school students. Results. Multiple regression analysis revealed associations between depression and gender, and several JTCI domains and facets. In line with previous findings in adults, high Harm Avoidance and low Self-Directedness emerged as the strongest predictors of adolescent depressive symptoms. Further, in logistic regression analysis with the covariates JTCI, GSE and CES-D, the only significant variables predicting use/non-use were the CES-D and the temperament domain Reward Dependence. Conclusion. The results in this study revealed level of depressive symptoms as the strongest predictor of the use of the Internet based intervention and that personality might provide useful information about the users. |
format | Online Article Text |
id | pubmed-3426188 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2012 |
publisher | Hindawi Publishing Corporation |
record_format | MEDLINE/PubMed |
spelling | pubmed-34261882012-08-27 Does Personality Predict Depression and Use of an Internet-Based Intervention for Depression among Adolescents? Vangberg, Hans Christian B. Lillevoll, Kjersti R. Waterloo, Knut Eisemann, Martin Depress Res Treat Research Article Background. Focus upon depression and prevention of its occurrence among adolescents is increasing. Novel ways of dealing with this serious problem have become available especially by means of internet-based prevention and treatment programs of depression and anxiety. The use of Internet-based intervention programs among adolescents has revealed some difficulties in implementation that need to be further elucidated. The aim of this study is to investigate the association between personality and adolescent depression and the characteristics of users of an Internet-based intervention program. Method. The Junior Temperament and Character Inventory (JTCI), the General Self-Efficacy scale (GSE) and the Centre for Epidemiological Studies-Depression scale (CES-D) have been administered to a sample (n = 1234) of Norwegian senior high-school students. Results. Multiple regression analysis revealed associations between depression and gender, and several JTCI domains and facets. In line with previous findings in adults, high Harm Avoidance and low Self-Directedness emerged as the strongest predictors of adolescent depressive symptoms. Further, in logistic regression analysis with the covariates JTCI, GSE and CES-D, the only significant variables predicting use/non-use were the CES-D and the temperament domain Reward Dependence. Conclusion. The results in this study revealed level of depressive symptoms as the strongest predictor of the use of the Internet based intervention and that personality might provide useful information about the users. Hindawi Publishing Corporation 2012 2012-08-15 /pmc/articles/PMC3426188/ /pubmed/22928095 http://dx.doi.org/10.1155/2012/593068 Text en Copyright © 2012 Hans Christian B. Vangberg et al. https://creativecommons.org/licenses/by/3.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Vangberg, Hans Christian B. Lillevoll, Kjersti R. Waterloo, Knut Eisemann, Martin Does Personality Predict Depression and Use of an Internet-Based Intervention for Depression among Adolescents? |
title | Does Personality Predict Depression and Use of an Internet-Based Intervention for Depression among Adolescents? |
title_full | Does Personality Predict Depression and Use of an Internet-Based Intervention for Depression among Adolescents? |
title_fullStr | Does Personality Predict Depression and Use of an Internet-Based Intervention for Depression among Adolescents? |
title_full_unstemmed | Does Personality Predict Depression and Use of an Internet-Based Intervention for Depression among Adolescents? |
title_short | Does Personality Predict Depression and Use of an Internet-Based Intervention for Depression among Adolescents? |
title_sort | does personality predict depression and use of an internet-based intervention for depression among adolescents? |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3426188/ https://www.ncbi.nlm.nih.gov/pubmed/22928095 http://dx.doi.org/10.1155/2012/593068 |
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