System Dynamics Applications to Injury and Violence Prevention: a Systematic Review

Naumann, Rebecca B.; Austin, Anna E.; Sheble, Laura; Lich, Kristen Hassmiller

doi:10.1007/s40471-019-00200-w

Cited by 12 publications

(9 citation statements)

References 57 publications

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“…To capture any studies we may have missed with our search strategy, we also conducted manual searches for additional articles, including a “backward” reference search of included articles, a “forward” reference search of papers citing included articles, a search of reference lists of key literature reviews (Carey et al, 2015 ; McGill et al, 2021 ; Naumann et al, 2019 ; Nianogo & Arah, 2015 ), and a search of key journals that publish systems science papers and/or papers on domestic and gender-based violence (see Online Resource).…”

Section: Methodsmentioning

confidence: 99%

“…These causal diagrams are then translated into computational models to examine system behavior. Similar to ABM, SD modeling can be used to explore causal mechanisms and effects of potential interventions on the system over time, allowing the identification of potential leverage points for maximum population-level impact (Homer & Hirsch, 2006 ; Lich et al, 2013 ; Naumann et al, 2019 ). SD modeling has been used to explore the dynamics governing youth violence in urban areas (Bridgewater et al, 2011 ) and to inform decision-making about how best to scale up programs to support housing security among families involved in the child welfare system (Fowler et al, 2020 ).…”

Section: Introductionmentioning

confidence: 99%

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A Systematic Review of Systems Science Approaches to Understand and Address Domestic and Gender-Based Violence

et al. 2023

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Purpose We aimed to synthesize insights from systems science approaches applied to domestic and gender-based violence. Methods We conducted a systematic review of systems science studies (systems thinking, group model-building, agent-based modeling [ABM], system dynamics [SD] modeling, social network analysis [SNA], and network analysis [NA]) applied to domestic or gender-based violence, including victimization, perpetration, prevention, and community responses. We used blinded review to identify papers meeting our inclusion criteria (i.e., peer-reviewed journal article or published book chapter that described a systems science approach to domestic or gender-based violence, broadly defined) and assessed the quality and transparency of each study. Results Our search yielded 1,841 studies, and 74 studies met our inclusion criteria (45 SNA, 12 NA, 8 ABM, and 3 SD). Although research aims varied across study types, the included studies highlighted social network influences on risks for domestic violence, clustering of risk factors and violence experiences, and potential targets for intervention. We assessed the quality of the included studies as moderate, though only a minority adhered to best practices in model development and dissemination, including stakeholder engagement and sharing of model code. Conclusions Systems science approaches for the study of domestic and gender-based violence have shed light on the complex processes that characterize domestic violence and its broader context. Future research in this area should include greater dialogue between different types of systems science approaches, consideration of peer and family influences in the same models, and expanded use of best practices, including continued engagement of community stakeholders. Supplementary Information The online version contains supplementary material available at 10.1007/s10896-023-00578-8.

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Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A Systematic Review of Systems Science Approaches to Understand and Address Domestic and Gender-Based Violence

et al. 2023

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“…For instance, systems thinking based on complex adaptive systems with system dynamics mapping has been used to inform large-scale change related to guideline implementation in Canada ( 13 ) and various health services outcomes in the US Veterans Administration system ( 163 , 166 ). A review of system dynamics applications in injury prevention research concluded that building capacity for system dynamics can support stakeholder engagement and policy analysis ( 115 ). Other researchers have demonstrated the usefulness of iterative engineering approaches to successful program D&I ( 135 ).…”

Section: A Narrative Review Of the D4ds Literaturementioning

confidence: 99%

Designing for Dissemination and Sustainability to Promote Equitable Impacts on Health

Kwan

Brownson

Glasgow

et al. 2022

Annu. Rev. Public Health

104

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Designing for dissemination and sustainability (D4DS) refers to principles and methods for enhancing the fit between a health program, policy, or practice and the context in which it is intended to be adopted. In this article we first summarize the historical context of D4DS and justify the need to shift traditional health research and dissemination practices. We present a diverse literature according to a D4DS organizing schema and describe a variety of dissemination products, design processes and outcomes, and approaches to messaging, packaging, and distribution. D4DS design processes include stakeholder engagement, participatory codesign, and context and situation analysis, and leverage methods and frameworks from dissemination and implementation science, marketing and business, communications and visual arts, and systems science. Finally, we present eight recommendations to adopt a D4DS paradigm, reflecting shifts in ways of thinking, skills and approaches, and infrastructure and systems for training and evaluation. Expected final online publication date for the Annual Review of Public Health, Volume 43 is April 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

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“…The principle hallmarks of ABM that distinguish it from other types of complex systems approaches include nonrandom mixing among autonomous, heterogeneous agents that can dynamically adapt their behavior over time to produce emergent patterns that cannot necessarily be predicted from the model’s behavioral rules (Luke & Stamatakis, 2012). In contrast, SD modeling is an aggregate approach that uses differential equations to interrogate the dynamics of a system, including feedback loops and transitions between homogeneous states (Naumann et al, 2019). Similar to ABM, SNA accounts for nonrandom interactions between entities and can be used to analyze characteristics of the network structure and how behaviors and health outcomes spread in social networks (Valente, 2010).…”

Section: Overview Of Agent-based Modelingmentioning

confidence: 99%

Applications of agent-based modeling in trauma research.

Tracy¹,

Gordis²,

Strully³

et al. 2023

Psychological Trauma: Theory, Research, Practice, and Policy

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Objective: Trauma, violence, and their consequences for population health are shaped by complex, intersecting forces across the life span. We aimed to illustrate the strengths of agent-based modeling (ABM), a computational approach in which population-level patterns emerge from the behaviors and interactions of simulated individuals, for advancing trauma research; Method: We provide an overview of agent-based modeling for trauma research, including a discussion of the model development process, ABM as a complement to other causal inference and complex systems approaches in trauma research, and past ABM applications in the trauma literature; Results: We use existing ABM applications to illustrate the strengths of ABM for trauma research, including incorporating interactions between individuals, simulating processes across multiple scales, examining life-course effects, testing alternate theories, comparing intervention strategies in a virtual laboratory, and guiding decision making. We also discuss the challenges of applying ABM to trauma research and offer specific suggestions for incorporating ABM into future studies of trauma and violence; Conclusion: Agent-based modeling is a useful complement to other methodological advances in trauma research. We recommend a more widespread adoption of ABM, particularly for research into patterns and consequences of individual traumatic experiences across the life course and understanding the effects of interventions that may be influenced by social norms and social network structures. Clinical Impact StatementThis article provides an overview of agent-based modeling (ABM), including its strengths, challenges, and future directions in trauma research. ABM approaches can account for the complex, multilevel nature of trauma and violence exposure and their population health consequences across the life course, enabling insight into optimal intervention strategies and guiding decision making. Past ABM studies in the trauma literature have mostly focused on disaster preparedness, postdisaster planning, and addressing community violence. More widespread use of ABM in trauma research, particularly applied to childhood maltreatment and domestic violence, may enhance our understanding and prevention of trauma and its consequences.

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System Dynamics Applications to Injury and Violence Prevention: a Systematic Review

Cited by 12 publications

References 57 publications

A Systematic Review of Systems Science Approaches to Understand and Address Domestic and Gender-Based Violence

A Systematic Review of Systems Science Approaches to Understand and Address Domestic and Gender-Based Violence

Designing for Dissemination and Sustainability to Promote Equitable Impacts on Health

Applications of agent-based modeling in trauma research.

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