Using community-based system dynamics modeling to understand the complex systems that influence health in cities: The SALURBAL study

Langellier, Brent A.; Kuhlberg, Jill; Ballard, Ellis; Slesinski, Claire; Stankov, Ivana; Meisel, José D.; Kroker-Lobos, María F; Sarmiento, Olga L.; Caiaffa, Waleska Teixeira; Roux, Ana V. Diez

doi:10.1016/j.healthplace.2019.102215

Cited by 56 publications

(74 citation statements)

References 43 publications

(51 reference statements)

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“…SD can be used to model the public's mental health and to understand the impact that support measures and care resources can have at a community level. A small number of SD models have been used to evaluate public health policies for the management of mental health (Langellier et al, 2019;Rutter et al, 2017), however there are opportunities to extend modelling efforts in this area, especially in community-based SD. HS models that combine SD with ABM to represent behavioural aspects related to social distancing would be also useful.…”

Section: Decision 11: Health and Well Beingmentioning

confidence: 99%

How simulation modelling can help reduce the impact of COVID-19

Currie

Fowler

Kotiadis

et al. 2020

Journal of Simulation

365

273

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Modelling has been used extensively by all national governments and the World Health Organisation in deciding on the best strategies to pursue in mitigating the effects of COVID-19. Principally these have been epidemiological models aimed at understanding the spread of the disease and the impacts of different interventions. But a global pandemic generates a large number of problems and questions, not just those related to disease transmission, and each requires a different model to find the best solution. In this article we identify challenges resulting from the COVID-19 pandemic and discuss how simulation modelling could help to support decision-makers in making the most informed decisions. Modellers should see the article as a call to arms and decision-makers as a guide to what support is available from the simulation community. ARTICLE HISTORY

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Section: Decision 11: Health and Well Beingmentioning

confidence: 99%

How simulation modelling can help reduce the impact of COVID-19

Currie

Fowler

Kotiadis

et al. 2020

Journal of Simulation

365

273

View full text Add to dashboard Cite

show abstract

“…There are many ways to support effective knowledge to policy translation [ 12 ], and recent proposals suggest exploring the use of community-based system dynamics (CBSD) to support this process in the context of urban health [ 1 , 13 , 14 ]. System dynamics provides an approach to explicitly model the structure of a system from the endogenous (or feedback) view, and to develop insights about how those structures drive that system’s behaviour [ 15 ].…”

Section: Introductionmentioning

confidence: 99%

Promoting knowledge to policy translation for urban health using community-based system dynamics in Brazil

Morais

Kuhlberg²,

Ballard

et al. 2021

Health Res Policy Sys

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Background Effectively bridging the knowledge–policy gap to support the development of evidence-based policies that promote health and well-being remains a challenge for both the research and policy communities. Community-based system dynamics (CBSD) is a participatory modelling approach that aims to build stakeholders’ capacity to learn and address complex problems collaboratively. However, limited evidence is available about the contributions of CBSD to knowledge-generating and policy processes across sectors and policy spheres. In the context of a multi-country research project focused on creating an evidence base to inform urban health policies across Latin America, a series of CBSD workshops convened stakeholders from research, policy-making, and other backgrounds working in food and transportation systems. Diverse participants were selected aiming to incorporate multiple perspectives relevant to understanding complex urban systems linked to food and transportation. This study focuses on one of these workshops, whose avenue was São Paulo, Brazil, assembling country-based participants representing local, regional, national, and international institutions with multidisciplinary backgrounds linked to food and transportation systems. Objective The aim of this case study is to explore the perceived influence of one of these workshops on attendees’ understandings of food and transportation systems and their relationship to healthy urban environments, with attention to the role of the workshop in supporting knowledge to policy translation for urban health. Methods We conducted 18 semi-structured qualitative interviews with attendees one year after their participation in a CBSD workshop held in São Paulo, Brazil. A framework method approach was used to code participants’ responses and identify emerging themes. Results Participants reported that the workshop’s group model-building activities influenced their understanding of the knowledge–policy process as it relates to food and transport systems. Workshop contributed to participants’ (1) abilities to engage with multisectoral stakeholders, (2) construct a shared language and understanding of urban challenges, (3) improve understanding of the interconnectedness across food and transportation systems, (4) facilitate dialogue across sectors, and (5) apply a systems thinking approach within their sector and professional context. Participants continued to draw on the tools developed during the workshop, and to apply systems thinking to their research and policy-making activities. Conclusions CBSD may offer valuable opportunities to connect the research sector to the policy-making process. This possibility may contribute to knowledge to policy translation in the interconnection between the urban context, food and transportation systems, and health.

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“…The CLD articulates key (locally specific) structures and feedback loops in the obesity system and often leads to new hypotheses, which are useful for further empirical research. GMB has demonstrated its usefulness in exploring sociocultural factors that affect health, including healthy eating, active living, and childhood obesity [ 25 – 29 ]. In addition to other GMB strategies implemented and described below, CLD was adopted as a method that is aptly applicable for exploring complex problems such as obesity and for uncovering visual and dynamic interconnections between factors contributing to childhood obesity.…”

Section: Introductionmentioning

confidence: 99%

Developing a Socioculturally Nuanced Systems Model of Childhood Obesity in Manhattan’s Chinese American Community via Group Model Building

et al. 2020

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The purpose of this study was to develop a qualitative and socioculturally tailored systems model of childhood obesity in the Chinese American community in Manhattan’s Chinatown. We utilized group model building (GMB) methodology as a form of participatory systems modeling. The study was conducted in Manhattan’s Chinatown community. We recruited 16 Chinese American adults from the community. GMB workshops engendered a causal loop diagram (CLD), the visualization of a complex systems model illustrating the structures, feedbacks, and interdependencies among socioculturally specific pathways underlying childhood obesity, in Manhattan’s Chinatown community. The analysis of CLD revealed that participants considered the following factors to influence childhood obesity: (1) traditional social norms affecting body image, how children are raised, parental pressure to study, and trust in health of traditional foods; (2) grandparents’ responsibility for children; (3) limited time availability of parents at home; and (4) a significant amount of children’s time spent indoors. GMB represents a novel method to understand the complexity of childhood obesity in culturally specific populations and contexts. The study identified sociocultural subsystems that may underlie the development and perpetuation of childhood obesity among Chinese American children. Insights from the study can be useful in the design of future empirical studies and interventions.

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Using community-based system dynamics modeling to understand the complex systems that influence health in cities: The SALURBAL study

Cited by 56 publications

References 43 publications

How simulation modelling can help reduce the impact of COVID-19

How simulation modelling can help reduce the impact of COVID-19

Promoting knowledge to policy translation for urban health using community-based system dynamics in Brazil

Developing a Socioculturally Nuanced Systems Model of Childhood Obesity in Manhattan’s Chinese American Community via Group Model Building

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