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.
Together with an international consortium of suicide researchers, I am reanalyzing national and international datasets with information on suicidal behaviour from a network perspective. This project will be called the SUPER project (Suicide Prevention by Extending Research). In the Netherlands, there are several large databases such as the NESDA (Netherlands Study of Depression and Anxiety). I will also have access to international data bases, for example from the Suicidal behavior research laboratory at Glasgow University.
By applying networkanalysis to these data sets I hope to visualize and quantify the complex associations between many different symptoms and their relation with suicidal behaviour. This will result in a better understanding of suicidal behavior and of new directions for prevention and research.