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Article

Sound Decision Making in Uncertain Times: Can Systems Modelling Be Useful for Informing Policy and Planning for Suicide Prevention?

1
Brain and Mind Centre, Faculty of Medicine and Health, University of Sydney, Sydney, NSW 2006, Australia
2
Computer Simulation & Advanced Research Technologies (CSART), Sydney, NSW 2021, Australia
3
Medical School, University of Western Australia, Perth, WA 6009, Australia
4
WA Primary Health Alliance, Perth, WA 6008, Australia
5
School of Computer, Data and Mathematical Sciences, Western Sydney University, Penrith, NSW 2751, Australia
6
St Vincent’s Clinical School, University of New South Wales, Sydney, NSW 2052, Australia
*
Author to whom correspondence should be addressed.
Academic Editors: Jo Robinson and Nicole Hill
Int. J. Environ. Res. Public Health 2022, 19(3), 1468; https://doi.org/10.3390/ijerph19031468
Received: 15 December 2021 / Revised: 21 January 2022 / Accepted: 24 January 2022 / Published: 27 January 2022
(This article belongs to the Special Issue Novel Approaches to Suicide Prevention)
The COVID-19 pandemic demonstrated the significant value of systems modelling in supporting proactive and effective public health decision making despite the complexities and uncertainties that characterise an evolving crisis. The same approach is possible in the field of mental health. However, a commonly levelled (but misguided) criticism prevents systems modelling from being more routinely adopted, namely, that the presence of uncertainty around key model input parameters renders a model useless. This study explored whether radically different simulated trajectories of suicide would result in different advice to decision makers regarding the optimal strategy to mitigate the impacts of the pandemic on mental health. Using an existing system dynamics model developed in August 2020 for a regional catchment of Western Australia, four scenarios were simulated to model the possible effect of the COVID-19 pandemic on levels of psychological distress. The scenarios produced a range of projected impacts on suicide deaths, ranging from a relatively small to a dramatic increase. Discordance in the sets of best-performing intervention scenarios across the divergent COVID-mental health trajectories was assessed by comparing differences in projected numbers of suicides between the baseline scenario and each of 286 possible intervention scenarios calculated for two time horizons; 2026 and 2041. The best performing intervention combinations over the period 2021–2041 (i.e., post-suicide attempt assertive aftercare, community support programs to increase community connectedness, and technology enabled care coordination) were highly consistent across all four COVID-19 mental health trajectories, reducing suicide deaths by between 23.9–24.6% against the baseline. However, the ranking of best performing intervention combinations does alter depending on the time horizon under consideration due to non-linear intervention impacts. These findings suggest that systems models can retain value in informing robust decision making despite uncertainty in the trajectories of population mental health outcomes. It is recommended that the time horizon under consideration be sufficiently long to capture the full effects of interventions, and efforts should be made to achieve more timely tracking and access to key population mental health indicators to inform model refinements over time and reduce uncertainty in mental health policy and planning decisions. View Full-Text
Keywords: suicide prevention; strategic planning; decision analysis; systems modelling; simulation; mental health suicide prevention; strategic planning; decision analysis; systems modelling; simulation; mental health
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MDPI and ACS Style

Occhipinti, J.-A.; Rose, D.; Skinner, A.; Rock, D.; Song, Y.J.C.; Prodan, A.; Rosenberg, S.; Freebairn, L.; Vacher, C.; Hickie, I.B. Sound Decision Making in Uncertain Times: Can Systems Modelling Be Useful for Informing Policy and Planning for Suicide Prevention? Int. J. Environ. Res. Public Health 2022, 19, 1468. https://doi.org/10.3390/ijerph19031468

AMA Style

Occhipinti J-A, Rose D, Skinner A, Rock D, Song YJC, Prodan A, Rosenberg S, Freebairn L, Vacher C, Hickie IB. Sound Decision Making in Uncertain Times: Can Systems Modelling Be Useful for Informing Policy and Planning for Suicide Prevention? International Journal of Environmental Research and Public Health. 2022; 19(3):1468. https://doi.org/10.3390/ijerph19031468

Chicago/Turabian Style

Occhipinti, Jo-An, Danya Rose, Adam Skinner, Daniel Rock, Yun J.C. Song, Ante Prodan, Sebastian Rosenberg, Louise Freebairn, Catherine Vacher, and Ian B. Hickie. 2022. "Sound Decision Making in Uncertain Times: Can Systems Modelling Be Useful for Informing Policy and Planning for Suicide Prevention?" International Journal of Environmental Research and Public Health 19, no. 3: 1468. https://doi.org/10.3390/ijerph19031468

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