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Network Analysis: A Novel Approach to Understand Suicidal Behaviour

Although suicide is a major public health issue worldwide, we understand little of the onset and development of suicidal behaviour. Suicidal behaviour is argued to be the end result of the complex interaction between psychological, social and biological factors. Epidemiological studies resulted in a...

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Detalles Bibliográficos
Autor principal: de Beurs, Derek
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5369055/
http://dx.doi.org/10.3390/ijerph14030219
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author de Beurs, Derek
author_facet de Beurs, Derek
author_sort de Beurs, Derek
collection PubMed
description Although suicide is a major public health issue worldwide, we understand little of the onset and development of suicidal behaviour. Suicidal behaviour is argued to be the end result of the complex interaction between psychological, social and biological factors. Epidemiological studies resulted in a range of risk factors for suicidal behaviour, but we do not yet understand how their interaction increases the risk for suicidal behaviour. A new approach called network analysis can help us better understand this process as it allows us to visualize and quantify the complex association between many different symptoms or risk factors. A network analysis of data containing information on suicidal patients can help us understand how risk factors interact and how their interaction is related to suicidal thoughts and behaviour. A network perspective has been successfully applied to the field of depression and psychosis, but not yet to the field of suicidology. In this theoretical article, I will introduce the concept of network analysis to the field of suicide prevention, and offer directions for future applications and studies.
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spelling pubmed-53690552017-04-05 Network Analysis: A Novel Approach to Understand Suicidal Behaviour de Beurs, Derek Int J Environ Res Public Health Perspective Although suicide is a major public health issue worldwide, we understand little of the onset and development of suicidal behaviour. Suicidal behaviour is argued to be the end result of the complex interaction between psychological, social and biological factors. Epidemiological studies resulted in a range of risk factors for suicidal behaviour, but we do not yet understand how their interaction increases the risk for suicidal behaviour. A new approach called network analysis can help us better understand this process as it allows us to visualize and quantify the complex association between many different symptoms or risk factors. A network analysis of data containing information on suicidal patients can help us understand how risk factors interact and how their interaction is related to suicidal thoughts and behaviour. A network perspective has been successfully applied to the field of depression and psychosis, but not yet to the field of suicidology. In this theoretical article, I will introduce the concept of network analysis to the field of suicide prevention, and offer directions for future applications and studies. MDPI 2017-02-23 2017-03 /pmc/articles/PMC5369055/ http://dx.doi.org/10.3390/ijerph14030219 Text en © 2017 by the author. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Perspective
de Beurs, Derek
Network Analysis: A Novel Approach to Understand Suicidal Behaviour
title Network Analysis: A Novel Approach to Understand Suicidal Behaviour
title_full Network Analysis: A Novel Approach to Understand Suicidal Behaviour
title_fullStr Network Analysis: A Novel Approach to Understand Suicidal Behaviour
title_full_unstemmed Network Analysis: A Novel Approach to Understand Suicidal Behaviour
title_short Network Analysis: A Novel Approach to Understand Suicidal Behaviour
title_sort network analysis: a novel approach to understand suicidal behaviour
topic Perspective
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5369055/
http://dx.doi.org/10.3390/ijerph14030219
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