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Integrating complex systems science into road safety research and practice, Part 2: Applying systems tools to the problem of increasing pedestrian death rates
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December 17 2019
Source: Inj Prev. 26(5):424-431 -
Alternative Title:Inj Prev
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Personal Author:
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Description:Objectives:
To provide a specific example of how systems dynamics tools can increase understanding of stakeholder “mental models” and generate robust systems-based hypotheses about the escalating problem of rising pedestrian death rates in the U.S.
Methods:
We designed and facilitated two group model building (GMB) workshops. Participants generated causal loop diagrams (CLD) individually and in small groups to explore hypotheses concerning time-dynamic interacting factors underlying the increasing rates of pedestrian deaths. Using a grounded theory approach, research team members synthesized the structures and hypotheses into a single CLD.
Results:
CLDs from the 41 participants indicated four core factors hypothesized to have a direct impact on pedestrian fatalities: pedestrian-vehicle crashes, vehicle speed at the time of the crash, vehicle size/dimensions, and emergency response time. Participants diagrammed how actions and reactions impacted these proximal factors over time and led to ripple effects throughout a larger system to generate an increase in pedestrian deaths. Hypothesized contributing mechanisms fell within the following broad categories: community responses; research, policy, and industry influence; potential unintended consequences of responses to pedestrian deaths; and the role of sprawl.
Conclusions:
This application of systems science tools suggested several strategies for advancing injury prevention research and practice. The project generated robust hypotheses and advanced stakeholder communication and depth of understanding and engagement in this key issue. The CLD and GMB process detailed in this study provides a concrete example of how systems tools can be adopted and applied to a transportation safety topic.
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Pubmed ID:31848213
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Pubmed Central ID:PMC8126266
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