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Network Analysis: A Novel Approach to Understand Suicidal Behaviour

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  • Derek De Beurs

    (Netherlands Institute for Health Services Research (NIVEL), Otterstraat 118-124, 3513 CR Utrecht, The Netherlands)

Abstract

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.

Suggested Citation

  • Derek De Beurs, 2017. "Network Analysis: A Novel Approach to Understand Suicidal Behaviour," IJERPH, MDPI, vol. 14(3), pages 1-8, February.
  • Handle: RePEc:gam:jijerp:v:14:y:2017:i:3:p:219-:d:91286
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    References listed on IDEAS

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    1. Epskamp, Sacha & Cramer, Angélique O.J. & Waldorp, Lourens J. & Schmittmann, Verena D. & Borsboom, Denny, 2012. "qgraph: Network Visualizations of Relationships in Psychometric Data," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 48(i04).
    2. Maarten Bak & Marjan Drukker & Laila Hasmi & Jim van Os, 2016. "An n=1 Clinical Network Analysis of Symptoms and Treatment in Psychosis," PLOS ONE, Public Library of Science, vol. 11(9), pages 1-15, September.
    3. Berend Terluin & Michiel R de Boer & Henrica C W de Vet, 2016. "Differences in Connection Strength between Mental Symptoms Might Be Explained by Differences in Variance: Reanalysis of Network Data Did Not Confirm Staging," PLOS ONE, Public Library of Science, vol. 11(11), pages 1-12, November.
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