Article
Version 3
This version is not peer-reviewed
Network Analysis: A Novel Approach to Understand Suicidal Behavior
Version 1
: Received: 24 January 2017 / Approved: 25 January 2017 / Online: 25 January 2017 (17:19:48 CET)
Version 2 : Received: 8 February 2017 / Approved: 8 February 2017 / Online: 8 February 2017 (09:39:34 CET)
Version 3 : Received: 11 February 2017 / Approved: 13 February 2017 / Online: 13 February 2017 (11:04:49 CET)
Version 2 : Received: 8 February 2017 / Approved: 8 February 2017 / Online: 8 February 2017 (09:39:34 CET)
Version 3 : Received: 11 February 2017 / Approved: 13 February 2017 / Online: 13 February 2017 (11:04:49 CET)
A peer-reviewed article of this Preprint also exists.
de Beurs, D. Network Analysis: A Novel Approach to Understand Suicidal Behaviour. Int. J. Environ. Res. Public Health 2017, 14, 219. de Beurs, D. Network Analysis: A Novel Approach to Understand Suicidal Behaviour. Int. J. Environ. Res. Public Health 2017, 14, 219.
Journal reference: IJERPH 2017, 14, 219
DOI: 10.3390/ijerph14030219
Abstract
Although suicide is a major public health issue worldwide, we understand little of the onset and development of suicidal behavior. Suicidal behavior 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 behavior, but we do not yet understand how their interaction increases the risk for suicidal behavior. A new approach called network analysis can help us better understand this process as it allows to visualize and quantify complex association between many different symptoms or risk factors. A network analysis of data contain 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.
Subject Areas
suicide; network analysis; symptoms; personalized treatment
Copyright: 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.
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