System dynamics models of depression at the population level: a scoping review

Health Research Policy and Systems

Review

Eva Graham¹  Geneviève Gariépy²  Heather Orpana³ 

[1] Centre for Surveillance and Applied Research, Health Promotion and Chronic Disease Prevention Branch, Public Health Agency of Canada, 785 Carling Ave, Ottawa, ON, Canada;Dalla Lana School of Public Health, University of Toronto, Toronto, Canada;Centre for Surveillance and Applied Research, Health Promotion and Chronic Disease Prevention Branch, Public Health Agency of Canada, 785 Carling Ave, Ottawa, ON, Canada;Department of Social and Preventive Medicine, School of Public Health, University of Montreal, Montreal, Canada;Montreal Mental Health University Institute Research Center, Montreal, Canada;Centre for Surveillance and Applied Research, Health Promotion and Chronic Disease Prevention Branch, Public Health Agency of Canada, 785 Carling Ave, Ottawa, ON, Canada;School of Epidemiology and Public Health, University of Ottawa, Ottawa, Canada;

关键词: Depression;    System dynamics modelling;    Simulation modelling;    Scoping review;   

DOI  :  10.1186/s12961-023-00995-7

 received in 2022-07-05, accepted in 2023-05-12,  发布年份 2023

来源: Springer

【 摘 要 】

AimsDepression is a disease driven by dynamic processes both at the individual- and system-level. System dynamics (SD) models are a useful tool to capture this complexity, project the future prevalence of depression and understand the potential impact of interventions and policies. SD models have been used to model infectious and chronic disease, but rarely applied to mental health. This scoping review aimed to identify population-based SD models of depression and report on their modelling strategies and applications to policy and decision-making to inform research in this emergent field.MethodsWe searched articles in MEDLINE, Embase, PsychInfo, Scopus, MedXriv, and abstracts from the System Dynamics Society from inception to October 20, 2021 for studies of population-level SD models of depression. We extracted data on model purpose, elements of SD models, results, and interventions, and assessed the quality of reporting.ResultsWe identified 1899 records and found four studies that met the inclusion criteria. Studies used SD models to assess various system-level processes and interventions, including the impact of antidepressant use on population-level depression in Canada; the impact of recall error on lifetime estimates of depression in the USA; smoking-related outcomes among adults with and without depression in the USA; and the impact of increasing depression incidence and counselling rates on depression in Zimbabwe. Studies included diverse stocks and flows for depression severity, recurrence, and remittance, but all models included flows for incidence and recurrence of depression. Feedback loops were also present in all models. Three studies provided sufficient information for replicability.ConclusionsThe review highlights the usefulness of SD models to model the dynamics of population-level depression and inform policy and decision-making. These results can help guide future applications of SD models to depression at the population-level.

【 授权许可】

CC BY   
© Crown 2023

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