Considerations for Using Participatory Systems Modeling as a Tool for Implementation Mapping in Chronic Disease Prevention

• Published in: Annals of epidemiology 2024-12
• Main Authors: Moore, Travis R., Hennessy, Erin, Chusan, Yuilyn Chang, Ashcraft, Laura Ellen, Economos, Christina D.
• Format: Article
• Language: English
• Subjects: community-engaged research; Epidemiology; implementation mapping; implementation science; participatory systems modeling; systems thinking
• ISSN: 1047-2797; 1873-2585; 1873-2585
• DOI: 10.1016/j.annepidem.2024.12.002

Effective chronic disease prevention requires a systems approach to the design, implementation, and refinement of interventions that account for the complexity and interdependence of factors influencing health outcomes. This paper proposes the Participatory Implementation Systems Mapping (PISM) process, which combines participatory systems modeling with implementation strategy development to enhance intervention design and implementation planning. PISM leverages the collaborative efforts of researchers and community partners to analyze complex health systems, identify key determinants, and develop tailored interventions and strategies that are both adaptive and contextually relevant. The phases of the PISM process include strategize, innovate, operationalize, and assess. We describe and demonstrate how each phase contributes to the overall goal of effective and sustainable intervention implementation. We also address the challenges of data availability, model complexity, and resource constraints. We offer solutions such as innovative data collection methods and participatory model development to enhance the robustness and applicability of systems models. Through a case study on the development of a chronic disease prevention intervention, the paper illustrates the practical application of PISM and highlights its potential to guide epidemiologists and implementation scientists in developing interventions that are responsive to the complexities of real-world health systems. The conclusion calls for further research to refine participatory systems modeling techniques, overcome existing challenges in data availability, and expand the use of PISM in diverse public health contexts.