Modelling tool gives new insights into suicide prevention

Sax Institute researchers are part of an important new partnership that is showing how a groundbreaking modelling tool can predict the likely impact of a range of suicide prevention interventions in Australia.

The research, using a “what if” tool called dynamic simulation modelling, is being pioneered by the partnership involving Western Sydney University, The Brain and Mind Centre, The Sax Institute and research consultancy Synergia, has potential to guide future activity and investment in suicide prevention.

By bringing together disparate sources of data and information, the computer modelling creates a decision-support tool that can test the impact of different combinations of policies and interventions in the virtual world, before they are implemented in the real world.

The researchers tested  the likely impact of five planned suicide prevention population interventions in Australia over the 10 years from 2015 to 2025:

    • GP training
    • Coordinated aftercare in those who have attempted suicide
    • School-based mental health literacy programs
    • Brief-contact interventions in hospital settings
    • Pscyhosocial treatment approaches

Their findings in Public Health Research & Practice showed that the largest reductions in suicide were associated with GP training (6%) and coordinated aftercare approaches (4%).

While the other interventions had negligible impacts on suicide trends when simulated individually, when combined they prevented an estimated at 12% of suicides, which the researchers said fell short of the National Mental Health Commission’s target of reducing suicides and suicide attempts by 50% over the next decade.

Suicide research demonstrates value of modelling

The researchers said the findings highlighted the value of system dynamic modelling methods for managing complex public health issues such as suicide.

“The model demonstrates a potential platform for integrating diverse evidence sources into an analytic tool that can allow policy makers to explore the likely impact of different policy and intervention scenarios over the short and longer term in a robust, risk-free and low-cost way,” they wrote. “That is, it can be used to conduct virtual experiments where real-world studies may not be feasible.”

Such modelling had the potential to be used as a decision-support tool for policy makers and program planners for community suicide prevention actions, they wrote.

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