Early life predictors of adolescent suicidal thoughts and adverse outcomes in two population-based cohort studies.

<h4>Background</h4>Understanding suicidality has proven challenging given the complex aetiology in early childhood. Being able to accurately predict groups at increased risk of developing suicidal thoughts may aid in the development of targeted prevention programs that mitigate increased...

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Main Authors: Jennifer Dykxhoorn, Simon Hatcher, Marie-Hélène Roy-Gagnon, Ian Colman
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2017-01-01
Series:PLoS ONE
Online Access:https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0183182&type=printable
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author Jennifer Dykxhoorn
Simon Hatcher
Marie-Hélène Roy-Gagnon
Ian Colman
author_facet Jennifer Dykxhoorn
Simon Hatcher
Marie-Hélène Roy-Gagnon
Ian Colman
author_sort Jennifer Dykxhoorn
collection DOAJ
description <h4>Background</h4>Understanding suicidality has proven challenging given the complex aetiology in early childhood. Being able to accurately predict groups at increased risk of developing suicidal thoughts may aid in the development of targeted prevention programs that mitigate increased vulnerability. Further, the predictors of suicidal thoughts may be shared with other outcomes in adolescence. Previous research has linked many factors to suicidality, so the objective of this study was to consider how these factors may act together to increase risk of suicidal thoughts and other non-mental health outcomes.<h4>Methods</h4>Two longitudinal datasets were used in this analysis: the National Longitudinal Survey of Children and Youth (NLSCY) and the Avon Longitudinal Survey of Parents and Children (ALSPAC). A Classification and Regression Tree model comprised of 75 factors describing early childhood was constructed to identify subgroups of adolescents at high risk of suicidal thoughts in the NLSCY and was validated in ALSPAC. These subgroups were investigated to see if they also had elevated rates of antisocial behaviour, substance misuse, poor physical health, poor mental health, risky health behaviours, and/or poor academic performance.<h4>Results</h4>The sensitivity was calculated to be 22·7%, specificity was 89·2%, positive predictive value 17·8%, and negative predictive value 91·8% and had similar accuracy in the validation dataset. The models were better at predicting other adverse outcomes compared to suicidal thoughts.<h4>Conclusion</h4>There are groups of risk factors present in early life that can predict higher risk of suicidality in adolescence. Notably, these factors were also predictive of a range of adverse outcomes in adolescence.
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spelling doaj-art-c0fa2d98b71d47f5a600f13263071eed2025-08-20T03:04:38ZengPublic Library of Science (PLoS)PLoS ONE1932-62032017-01-01128e018318210.1371/journal.pone.0183182Early life predictors of adolescent suicidal thoughts and adverse outcomes in two population-based cohort studies.Jennifer DykxhoornSimon HatcherMarie-Hélène Roy-GagnonIan Colman<h4>Background</h4>Understanding suicidality has proven challenging given the complex aetiology in early childhood. Being able to accurately predict groups at increased risk of developing suicidal thoughts may aid in the development of targeted prevention programs that mitigate increased vulnerability. Further, the predictors of suicidal thoughts may be shared with other outcomes in adolescence. Previous research has linked many factors to suicidality, so the objective of this study was to consider how these factors may act together to increase risk of suicidal thoughts and other non-mental health outcomes.<h4>Methods</h4>Two longitudinal datasets were used in this analysis: the National Longitudinal Survey of Children and Youth (NLSCY) and the Avon Longitudinal Survey of Parents and Children (ALSPAC). A Classification and Regression Tree model comprised of 75 factors describing early childhood was constructed to identify subgroups of adolescents at high risk of suicidal thoughts in the NLSCY and was validated in ALSPAC. These subgroups were investigated to see if they also had elevated rates of antisocial behaviour, substance misuse, poor physical health, poor mental health, risky health behaviours, and/or poor academic performance.<h4>Results</h4>The sensitivity was calculated to be 22·7%, specificity was 89·2%, positive predictive value 17·8%, and negative predictive value 91·8% and had similar accuracy in the validation dataset. The models were better at predicting other adverse outcomes compared to suicidal thoughts.<h4>Conclusion</h4>There are groups of risk factors present in early life that can predict higher risk of suicidality in adolescence. Notably, these factors were also predictive of a range of adverse outcomes in adolescence.https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0183182&type=printable
spellingShingle Jennifer Dykxhoorn
Simon Hatcher
Marie-Hélène Roy-Gagnon
Ian Colman
Early life predictors of adolescent suicidal thoughts and adverse outcomes in two population-based cohort studies.
PLoS ONE
title Early life predictors of adolescent suicidal thoughts and adverse outcomes in two population-based cohort studies.
title_full Early life predictors of adolescent suicidal thoughts and adverse outcomes in two population-based cohort studies.
title_fullStr Early life predictors of adolescent suicidal thoughts and adverse outcomes in two population-based cohort studies.
title_full_unstemmed Early life predictors of adolescent suicidal thoughts and adverse outcomes in two population-based cohort studies.
title_short Early life predictors of adolescent suicidal thoughts and adverse outcomes in two population-based cohort studies.
title_sort early life predictors of adolescent suicidal thoughts and adverse outcomes in two population based cohort studies
url https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0183182&type=printable
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AT marieheleneroygagnon earlylifepredictorsofadolescentsuicidalthoughtsandadverseoutcomesintwopopulationbasedcohortstudies
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