Applications of Agent-Based Modeling in Trauma Research

被引:4
作者
Tracy, Melissa [1 ]
Gordis, Elana [2 ]
Strully, Kate [3 ]
Marshall, Brandon D. L. [4 ]
Cerda, Magdalena [5 ]
机构
[1] SUNY Albany, Dept Epidemiol & Biostat, Rensselaer, NY 12144 USA
[2] SUNY Albany, Dept Psychol, Rensselaer, NY 12144 USA
[3] SUNY Albany, Dept Sociol, Rensselaer, NY 12144 USA
[4] Brown Univ, Dept Epidemiol, Sch Publ Hlth, Providence, RI 02912 USA
[5] NYU, Dept Populat Hlth, Grossman Sch Med, New York, NY 10003 USA
基金
美国国家卫生研究院;
关键词
agent-based modeling; complex systems; simulation; trauma; violence; POSTTRAUMATIC-STRESS-DISORDER; PUBLIC-HEALTH; PARTICIPATORY RESEARCH; SYSTEMS SCIENCE; VIOLENCE; EPIDEMIOLOGY; SIMULATION; SYMPTOMS; EXPOSURE; DISASTER;
D O I
10.1037/tra0001375
中图分类号
B849 [应用心理学];
学科分类号
040203 ;
摘要
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 Statement This 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.
引用
收藏
页码:939 / 950
页数:12
相关论文
共 108 条
[41]   The ODD Protocol for Describing Agent-Based and Other Simulation Models: A Second Update to Improve Clarity, Replication, and Structural Realism [J].
Grimm, Volker ;
Railsback, Steven F. ;
Vincenot, Christian E. ;
Berger, Uta ;
Gallagher, Cara ;
DeAngelis, Donald L. ;
Edmonds, Bruce ;
Ge, Jiaqi ;
Giske, Jarl ;
Groeneveld, Juergen ;
Johnston, Alice S. A. ;
Milles, Alexander ;
Nabe-Nielsen, Jacob ;
Polhill, J. Gareth ;
Radchuk, Viktoriia ;
Rohwaeder, Marie-Sophie ;
Stillman, Richard A. ;
Thiele, Jan C. ;
Ayllon, Daniel .
JASSS-THE JOURNAL OF ARTIFICIAL SOCIETIES AND SOCIAL SIMULATION, 2020, 23 (02)
[42]   Towards better modelling and decision support: Documenting model development, testing, and analysis using TRACE [J].
Grimm, Volker ;
Augusiak, Jacqueline ;
Focks, Andreas ;
Frank, Beatrice M. ;
Gabsi, Faten ;
Johnston, Alice S. A. ;
Liu, Chun ;
Martin, Benjamin T. ;
Meli, Mattia ;
Radchuk, Viktoriia ;
Thorbek, Pernille ;
Railsback, Steven F. .
ECOLOGICAL MODELLING, 2014, 280 :129-139
[43]   The ODD protocol A review and first update [J].
Grimm, Volker ;
Berger, Uta ;
DeAngelis, Donald L. ;
Polhill, J. Gary ;
Giske, Jarl ;
Railsback, Steven F. .
ECOLOGICAL MODELLING, 2010, 221 (23) :2760-2768
[44]   Simulating Crime Prevention Strategies: A Look at the Possibilities [J].
Groff, Elizabeth ;
Birks, Dan .
POLICING-A JOURNAL OF POLICY AND PRACTICE, 2008, 2 (02) :175-184
[45]   Simulation for theory testing and experimentation: An example using routine activity theory and street robbery [J].
Groff, Elizabeth R. .
JOURNAL OF QUANTITATIVE CRIMINOLOGY, 2007, 23 (02) :75-103
[46]   An Agent-Based Model for Addressing the Impact of a Disaster on Access to Primary Care Services [J].
Guclu, Hasan ;
Kumar, Supriya ;
Galloway, David ;
Krauland, Mary ;
Sood, Rishi ;
Bocour, Angelica ;
Hershey, Tina Batra ;
van Nostrand, Elizabeth ;
Potter, Margaret .
DISASTER MEDICINE AND PUBLIC HEALTH PREPAREDNESS, 2016, 10 (03) :386-393
[47]   What Does it Mean to be Trauma-Informed? A Multi-System Perspective from Practitioners Serving the Community [J].
Guevara, Ana Maria Melendez ;
Johnson, Sarah Lindstrom ;
Elam, Kit ;
Rivas, Tristyn ;
Berendzen, Hannah ;
Gal-Szabo, Diana E. .
JOURNAL OF CHILD AND FAMILY STUDIES, 2021, 30 (11) :2860-2876
[48]  
Hammond RA, 2015, ASSESSING THE USE OF AGENT-BASED MODELS FOR TOBACCO REGULATION, P161
[49]   Unraveling the complexity of human behavior and urbanization on community vulnerability to floods [J].
Hemmati, Mona ;
Mahmoud, Hussam N. ;
Ellingwood, Bruce R. ;
Crooks, Andrew T. .
SCIENTIFIC REPORTS, 2021, 11 (01)
[50]   Invited Commentary: Agent-Based Models for Causal Inference-Reweighting Data and Theory in Epidemiology [J].
Hernan, Miguel A. .
AMERICAN JOURNAL OF EPIDEMIOLOGY, 2015, 181 (02) :103-105