Assessing the efficacy of group model building workshops in an applied setting through purposive text analysis

Valcourt, Nicholas; Walters, Jeffrey P.; Javernick‐Will, Amy; Linden, Karl G.

doi:10.1002/sdr.1657

Cited by 18 publications

(14 citation statements)

References 47 publications

(62 reference statements)

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“…Since the codification of the idea of CBSD, many of its applications in public health have aimed to generate insights about a particular complex problem, through the construction of a shared language and broad shared understanding of the problems stakeholders desire to change, using system dynamics modelling tools [ 22 – 24 ]. A number of studies have explored the impact of group model-building processes on participant mental models and planning outcomes [ 25 – 29 ], and recent studies have explored community and programmatic factors influencing the adoption of system dynamics approaches for health policy [ 30 ]. However, to our knowledge, no study has focused on exploring the contributions of a CBSD-specific approach to knowledge to policy translation by facilitating discussion and analysis of complex problems among participants.…”

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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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

View full text Add to dashboard Cite

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“…System dynamics simulation models can be used for in silico experimentation to preliminarily test hypotheses when direct experimentation is impractical or unethical (Lombardo et al, 2021). These approaches, particularly diagram-based methods like causal-loop diagramming, allow for the integration of heterogeneous types of variables, such as the interactions between social support and biophysical (Valcourt et al, 2020). Simulation modeling also requires either time series data or some other basis for determining parameter values, which can limit its utility.…”

Section: Discussionmentioning

confidence: 99%

System dynamics modeling for traumatic brain injury: Mini-review of applications

Kenzie

Parks

Carney

et al. 2022

Front. Bioeng. Biotechnol.

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Traumatic brain injury (TBI) is a highly complex phenomenon involving a cascade of disruptions across biomechanical, neurochemical, neurological, cognitive, emotional, and social systems. Researchers and clinicians urgently need a rigorous conceptualization of brain injury that encompasses nonlinear and mutually causal relations among the factors involved, as well as sources of individual variation in recovery trajectories. System dynamics, an approach from systems science, has been used for decades in fields such as management and ecology to model nonlinear feedback dynamics in complex systems. In this mini-review, we summarize some recent uses of this approach to better understand acute injury mechanisms, recovery dynamics, and care delivery for TBI. We conclude that diagram-based approaches like causal-loop diagramming have the potential to support the development of a shared paradigm of TBI that incorporates social support aspects of recovery. When developed using adequate data from large-scale studies, simulation modeling presents opportunities for improving individualized treatment and care delivery.

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“…After all transcripts were coded, we ran a query using the codes related to causal structure (i.e., causal link, feedback loop, and archetype) to compile all relevant quotations. Quotations were compiled by participant rather than analyzed by individual participant because the aim was to develop a model that synthesized stakeholder perspectives [ 21 ]. The query report was then reviewed and all causal structures were entered into tables listing variables to be included in the model and causal links connecting them.…”

Section: Methodsmentioning

confidence: 99%

“…This change made out of necessity resulted in several modeling advantages. Because qualitative data were carefully abstracted into the model using an approach developed by Kim and Andersen [35] and subsequent researchers [17,21,[36][37][38][39], initial participants could share their perspective in an interview, which is likely a more familiar and convenient format for many stakeholders than a group modeling session. Abstracting causal information from individual qualitative interviews is time consuming, but is the most thorough way of gleaning models from qualitative data [17].…”

Section: Advantages and Limitations Of Modeling Approachmentioning

confidence: 99%

Long drives and red tape: mapping rural veteran access to primary care using causal-loop diagramming

Kenzie

Patzel

Nelson³

et al. 2022

BMC Health Serv Res

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Background Rural veterans experience more challenges than their urban peers in accessing primary care services, which can negatively impact their health and wellbeing. The factors driving this disparity are complex and involve patient, clinic, health system, community and policy influences. Federal policies over the last decade have relaxed requirements for some veterans to receive primary care services from community providers through their VA benefits, known as community care. Methods We used a participatory systems mapping approach involving causal-loop diagramming to identify interrelationships between variables underlying challenges to veteran access to primary care and potential opportunities for change—known as leverage points in systems science. Our methods involved a secondary analysis of semi-structured qualitative interviews with rural veterans, VA staff, non-VA clinic staff and providers who serve rural veterans, and veteran service officers (VSOs) in the Northwest region of the US, followed by a two-part participatory modeling session with a study advisory board. We then applied Meadows’s leverage point framework to identify and categorize potential interventions to improve rural veteran access to primary care. Results The final model illustrated challenges at the veteran, clinic, and system levels as experienced by stakeholders. Main components of the diagram pertained to the choice of VA or non-VA primary care, veteran satisfaction with the VA, enrollment in VA benefits and other insurance, community care authorization, reimbursement of non-VA care, referrals to specialty care, record sharing and communication between VA and non-VA providers, institutional stability of the VA, and staffing challenges. Fourteen interventions, including administrative and communications changes, were identified by analyzing the model using the leverage points framework. Conclusions Our findings illustrate how challenges rural veterans face accessing health care are interconnected and persist despite recent changes to federal law pertaining to the VA health care system in recent years. Systems mapping and modeling approaches such as causal-loop diagramming have potential for engaging stakeholders and supporting intervention and implementation planning.

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Assessing the efficacy of group model building workshops in an applied setting through purposive text analysis

Cited by 18 publications

References 47 publications

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

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

System dynamics modeling for traumatic brain injury: Mini-review of applications

Long drives and red tape: mapping rural veteran access to primary care using causal-loop diagramming

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