Abstract
In recent years, a number of different authors have stressed the usefulness of non-linear dynamic systems approach in suicide research and suicide prevention. This approach applies specific methods of time series analysis and, consequently, it requires a continuous and fine-meshed assessment of the processes under consideration. The technical means for this kind of process assessment and process analysis are now available. This paper outlines how suicidal dynamics can be monitored in high-risk patients by an Internet-based application for continuous self-assessment with integrated tools of non-linear time series analysis: the Synergetic Navigation System. This procedure is illustrated by data from a patient who attempted suicide at the end of a 90-day monitoring period. Additionally, future research topics and clinical applications of a non-linear dynamic systems approach in suicidology are discussed.
Highlights
Modeling psychopathological processes with non-linear dynamic systems has been suggested by numerous scholars (Schiepek and Tschacher, 1992; Barton, 1994; Belair et al, 1995; Ehlers, 1995; Heiby, 1995; Breakspear, 2006; Tschacher and Junghan, 2009; Haken and Schiepek, 2010; Bystritsky et al, 2012; Yang and Tsai, 2013)
Non-linear dynamic systems are referred to as dynamic because they exist over time and can realize processes, i.e., a dynamic system determines the evolution of a system over time given an initial state (Stam, 2005)
The results demonstrate how a suicidal process can be monitored by the algorithms available through the Synergetic Navigation System (SNS) and interpreted from a non-linear dynamic perspective
Summary
Modeling psychopathological processes with non-linear dynamic systems has been suggested by numerous scholars (Schiepek and Tschacher, 1992; Barton, 1994; Belair et al, 1995; Ehlers, 1995; Heiby, 1995; Breakspear, 2006; Tschacher and Junghan, 2009; Haken and Schiepek, 2010; Bystritsky et al, 2012; Yang and Tsai, 2013). Non-linear dynamic systems are an emerging field in suicidology (Mishara, 1996; Ramsay, 1997; Rogers, 2003; Large, 2010; Rogers and Lester, 2010; Schiepek et al, 2011b; Sawhney, 2012), contributing new perspectives on the emergence and prediction of suicide-related phenomena. Before discussing this any further, we introduce some basic concepts about non-linear dynamic systems (for a detailed description see Stam, 2005; Strunk and Schiepek, 2006). Non-linear dynamic systems are defined by four important characteristics (Strunk and Schiepek, 2006): first, they consist of at least one variable in the case of discrete processes or of at
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