Suicide is one of the leading causes of mortality among young people aged 15–24 globally. The suicide mortality rate is one of the indicators within the UN’s Sustainable Development Goal (SDG) 3, and the WHO Comprehensive Mental Health Action Plan (2013–2030) identifies young people as a high-risk group. Despite increasing investment in suicide prevention activities from many governments worldwide, we still do not know which interventions, policies, or programs, for which groups of young people, for how long and with what intensity could generate the greatest reductions in youth suicide rates. Progress in youth suicide prevention has been stalled by many factors including:
• A lack of involvement of young people in the design of interventions meaning that they are not youth-focused and, therefore, not acceptable to end-users.
• A lack of planning for the systematic uptake and implementation of strategies in the real world.
• Limited adequacy and accuracy of current methodological approaches (e.g. meta-analyses, regression models) which do not account for the interdependence of suicide risk factors as they operate across multiple levels (e.g. individual, social, health system); and consider the complexity of health systems and the influence of factors such as healthcare constraints.
SEYMOUR (System Dynamics Modelling in Suicide Prevention) offers a novel paradigm for guiding the efficient and effective deployment of national and global youth suicide prevention strategies using system dynamics modelling (SDM). SDM is a computer-assisted method that helps frame, test and simulate the causal processes and interactions that underlie complex systems or behaviours (such as suicide) to inform policy making. A unique selling point of SDM is that it may be guided by a participatory approach, which leverages empirical data together with the experiential knowledge of stakeholders, to inform model building, evaluation, and implementation.
The overall objective of SEYMOUR was to adopt participatory systems modelling to develop and evaluate a computational model to inform youth suicide prevention policy, planning and implementation in Australia and the UK.