ArticleAnnals of epidemiology2025
Considerations for using participatory systems modeling as a tool for implementation mapping in chronic disease prevention.
Article in Annals of epidemiology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
5 citing papers in PubMed.
- Advancing systems thinking in implementation science: An epidemiologic perspective.Annals of epidemiology · 2026Article
- Ethical challenges and opportunities for integrating predictive analytics in community-based overdose prevention.Lancet regional health. Americas · 2026Review
- Participatory system dynamics modeling: advancing equity through contextualized implementation science in global health.BMC global and public health · 2026Review
- Participatory systems modeling in implementation research: Exploring benefits, facilitators, and future needs.Journal of clinical and translational science · 2026Article
- A participatory systems approach for visualizing and testing implementation strategies and mechanisms: evidence adoption in community coalitions.Implementation science communications · 2025Article
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
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.
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Registered trials
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