Abstract for: Simulation of a 'suicidal mind': Using the Integrated Motivational Volitional model to demonstrate dynamic suicidal states.

Suicidal behaviors are characterized by complex, multi-factorial etiology. Dynamic simulation models (DSMs) are computational approaches that can explicitly capture salient dimensions of suicidal thinking and behavior. They also allow for testing interventions quickly, cheaply, and in a safe environment. This study describes the development of a DSM that describes the dynamics of suicidal thoughts and behaviors at an individual level based on several prominent theories of suicidality. We synthesize a theoretical model of suicidality from the Integrated Motivational-Volitional model of suicide, the Fluid Vulnerability Theory of suicide, and the Cusp-Catastrophe model from dynamical systems theory. Using this theory, we develop a DSM and validate the model through expert analysis and by recreating common patterns of suicidal behavior. We also investigate the effect of health services in various scenarios. The model’s behavior in response to varying parameters of interest was consistent with expectations. The model could recreate the ‘stable,’ ‘dysregulated,’ and ‘discontinuous’ nonlinear pathways proposed in prior research supporting the validity of the DSM and its underlying theoretical synthesis. Mental health service access resulted in stabilization of suicidal ideation, but the effect varied by frequency of contact. Our model demonstrates that DSMs can quantify and refine theories of suicidal behavior. This suggests potential for using DSMs in virtual case studies to assist clinical decision making and training, or to investigate population-level interventions. Suicide prevention research studies are often costly and pose a risk to trial participants. Completing tests in-silico is fast, cheap, and can direct researchers down the safest and most promising path before attempting real-world trials.