SYSTEM DYNAMICS MODELLING FOR SUICIDE PREVENTION

Globally, suicide is the second leading cause of death among young people aged 15-29. Many European countries have seen a sustained increase in youth suicide rates in recent years.

Despite the deployment of comprehensive and multilevel suicide prevention strategies, we still do not know which suicide prevention interventions, for which groups of young people, for how long, and with what intensity could generate the most significant reductions in youth suicide rates.

Therefore, we cannot efficiently and effectively inform decision-making in youth suicide prevention policy, planning and implementation.

Current methodological approaches (meta-analyses, regression models) for synthesizing and operationalising research evidence used to inform suicide prevention strategies have limited adequacy and accuracy because they do not: respond to real-time suicide data; account for the interrelationship, interdependence and nonlinearity of suicide risk factors as they operate across multiple levels (e.g. individual, social); consider the influence of factors such as healthcare constraints (access, capacity).

SEYMOUR offers a novel paradigm for guiding the efficient and effective deployment of national and global youth suicide prevention strategies through the use of system dynamics modelling (SDM).

SEYMOUR will develop and evaluate a novel SDM that will demonstrate which suicide prevention interventions could generate the most significant reductions in suicide rates among young people aged 12-25.

This will include an implementation blueprint to facilitate the transferability, internationalisation and adoption of the SDM as a decision-making tool in youth suicide prevention policy and practice in Europe and globally.

The conceptualisation, formulation, testing of the SDM; and, development of an implementation blueprint will take place during Years 1 and 2 at UoM. The validation of SDM in the UK and adaptation of the implementation strategy (WP4) will take place during Year 3.