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Reducing youth suicide: systems modelling and simulation to guide targeted investments across the determinants

BACKGROUND: Reducing suicidal behaviour (SB) is a critical public health issue globally. The complex interplay of social determinants, service system factors, population demographics, and behavioural dynamics makes it extraordinarily difficult for decision makers to determine the nature and balance...

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Autores principales: Occhipinti, Jo-An, Skinner, Adam, Iorfino, Frank, Lawson, Kenny, Sturgess, Julie, Burgess, Warren, Davenport, Tracey, Hudson, Danica, Hickie, Ian
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7952221/
https://www.ncbi.nlm.nih.gov/pubmed/33706764
http://dx.doi.org/10.1186/s12916-021-01935-4
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author Occhipinti, Jo-An
Skinner, Adam
Iorfino, Frank
Lawson, Kenny
Sturgess, Julie
Burgess, Warren
Davenport, Tracey
Hudson, Danica
Hickie, Ian
author_facet Occhipinti, Jo-An
Skinner, Adam
Iorfino, Frank
Lawson, Kenny
Sturgess, Julie
Burgess, Warren
Davenport, Tracey
Hudson, Danica
Hickie, Ian
author_sort Occhipinti, Jo-An
collection PubMed
description BACKGROUND: Reducing suicidal behaviour (SB) is a critical public health issue globally. The complex interplay of social determinants, service system factors, population demographics, and behavioural dynamics makes it extraordinarily difficult for decision makers to determine the nature and balance of investments required to have the greatest impacts on SB. Real-world experimentation to establish the optimal targeting, timing, scale, frequency, and intensity of investments required across the determinants is unfeasible. Therefore, this study harnesses systems modelling and simulation to guide population-level decision making that represent best strategic allocation of limited resources. METHODS: Using a participatory approach, and informed by a range of national, state, and local datasets, a system dynamics model was developed, tested, and validated for a regional population catchment. The model incorporated defined pathways from social determinants of mental health to psychological distress, mental health care, and SB. Intervention scenarios were investigated to forecast their impact on SB over a 20-year period. RESULTS: A combination of social connectedness programs, technology-enabled coordinated care, post-attempt assertive aftercare, reductions in childhood adversity, and increasing youth employment projected the greatest impacts on SB, particularly in a youth population, reducing self-harm hospitalisations (suicide attempts) by 28.5% (95% interval 26.3–30.8%) and suicide deaths by 29.3% (95% interval 27.1–31.5%). Introducing additional interventions beyond the best performing suite of interventions produced only marginal improvement in population level impacts, highlighting that ‘more is not necessarily better.’ CONCLUSION: Results indicate that targeted investments in addressing the social determinants and in mental health services provides the best opportunity to reduce SB and suicide. Systems modelling and simulation offers a robust approach to leveraging best available research, data, and expert knowledge in a way that helps decision makers respond to the unique characteristics and drivers of SB in their catchments and more effectively focus limited health resources. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12916-021-01935-4.
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spelling pubmed-79522212021-03-12 Reducing youth suicide: systems modelling and simulation to guide targeted investments across the determinants Occhipinti, Jo-An Skinner, Adam Iorfino, Frank Lawson, Kenny Sturgess, Julie Burgess, Warren Davenport, Tracey Hudson, Danica Hickie, Ian BMC Med Research Article BACKGROUND: Reducing suicidal behaviour (SB) is a critical public health issue globally. The complex interplay of social determinants, service system factors, population demographics, and behavioural dynamics makes it extraordinarily difficult for decision makers to determine the nature and balance of investments required to have the greatest impacts on SB. Real-world experimentation to establish the optimal targeting, timing, scale, frequency, and intensity of investments required across the determinants is unfeasible. Therefore, this study harnesses systems modelling and simulation to guide population-level decision making that represent best strategic allocation of limited resources. METHODS: Using a participatory approach, and informed by a range of national, state, and local datasets, a system dynamics model was developed, tested, and validated for a regional population catchment. The model incorporated defined pathways from social determinants of mental health to psychological distress, mental health care, and SB. Intervention scenarios were investigated to forecast their impact on SB over a 20-year period. RESULTS: A combination of social connectedness programs, technology-enabled coordinated care, post-attempt assertive aftercare, reductions in childhood adversity, and increasing youth employment projected the greatest impacts on SB, particularly in a youth population, reducing self-harm hospitalisations (suicide attempts) by 28.5% (95% interval 26.3–30.8%) and suicide deaths by 29.3% (95% interval 27.1–31.5%). Introducing additional interventions beyond the best performing suite of interventions produced only marginal improvement in population level impacts, highlighting that ‘more is not necessarily better.’ CONCLUSION: Results indicate that targeted investments in addressing the social determinants and in mental health services provides the best opportunity to reduce SB and suicide. Systems modelling and simulation offers a robust approach to leveraging best available research, data, and expert knowledge in a way that helps decision makers respond to the unique characteristics and drivers of SB in their catchments and more effectively focus limited health resources. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12916-021-01935-4. BioMed Central 2021-03-12 /pmc/articles/PMC7952221/ /pubmed/33706764 http://dx.doi.org/10.1186/s12916-021-01935-4 Text en © The Author(s) 2021 Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research Article
Occhipinti, Jo-An
Skinner, Adam
Iorfino, Frank
Lawson, Kenny
Sturgess, Julie
Burgess, Warren
Davenport, Tracey
Hudson, Danica
Hickie, Ian
Reducing youth suicide: systems modelling and simulation to guide targeted investments across the determinants
title Reducing youth suicide: systems modelling and simulation to guide targeted investments across the determinants
title_full Reducing youth suicide: systems modelling and simulation to guide targeted investments across the determinants
title_fullStr Reducing youth suicide: systems modelling and simulation to guide targeted investments across the determinants
title_full_unstemmed Reducing youth suicide: systems modelling and simulation to guide targeted investments across the determinants
title_short Reducing youth suicide: systems modelling and simulation to guide targeted investments across the determinants
title_sort reducing youth suicide: systems modelling and simulation to guide targeted investments across the determinants
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7952221/
https://www.ncbi.nlm.nih.gov/pubmed/33706764
http://dx.doi.org/10.1186/s12916-021-01935-4
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