Abstract

Public health scholarship has increasingly called for the use of system science approaches to understand complex problems, including the use of participatory engagement to inform the modeling process. Some system science traditions, specifically system dynamics modeling, have an established participatory practice tradition. Yet, there remains limited guidance on engagement strategies using other modeling approaches like agent-based models. Our objective is to describe how we engaged adolescent youth in co-building an agent-based model about physical activity. Specifically, we aim to describe how we communicated technical aspects of agent-based models, the participatory activities we developed, and the resulting visual diagrams that were produced. We implemented six sessions with nine adolescent participants. To make technical aspects more accessible, we used an analogy that linked core components of agent-based models to elements of storytelling. We also implemented novel, facilitated activities that engaged youth in the development, annotation, and review of graphs over time, geographical maps, and state charts. The process was well-received by the participants and helped inform the basic structure of an agent-based model. The resulting visual diagrams created space for deeper discussion among participants about patterns of daily activity, important places for physical activity, and interactions between social and built environments. This work lays a foundation to develop and refine engagement strategies, especially for translating qualitative insights into quantitative model specifications such as 'decision rules'.

Highlights

  • Understanding how to improve behaviors like physical activity is complex

  • The Decision Rules artifacts indicated that social interactions were likely influential in physical activity choices and more information was needed to operationalize the pathways and processes by which friends and family impact activity decisions on a day-to-day basis

  • Our team found storytelling to be a helpful analogy in communicating the technical aspects of agent-based models

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Summary

Introduction

Understanding how to improve behaviors like physical activity is complex. Many levels of influence, including individual motivations, interpersonal social networks, and built environments, interact to shape behavior over time. Scholars have called for the use of systems science and simulation modeling to help manage the complexity of this type of public health issue [1,2,3,4]. It is recommended that the simulation models are developed with stakeholders [1, 3, 5, 6], which has potential to produce better models, increase the social capital of communities, and improve the chance that a model successfully influences decision making [7]

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