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Updated: Jan 16, 2026

The Participant-Reported Implementation Update and Score PRIUS: A Novel Method for Capturing Implementation-Related Data Over Time
Published on: February 19, 2021
A participatory systems approach for visualizing and testing implementation strategies and mechanisms: evidence
Travis R Moore1, Yuilyn A Chang Chusan2, Mark Pachucki3
1Friedman School of Nutrition Science and Policy, Tufts University, Boston, MA, 02111, USA. Travis.Moore@Tufts.edu.
Background:
The strengths of Implementation Science can be further enhanced by embracing methods that account for the complexity of real-world systems, complementing its existing focus on translating evidence into practice. Systems science offers an approach to understanding the interactions, feedback loops, and non-linear relationships that drive implementation processes. Despite its potential, practical examples of systems methods for designing and linking implementation strategies to mechanisms remain scarce. This case study demonstrates how systems methods can help operationalize implementation strategies and mechanisms within the context of a project called the Feasibility of Network Interventions for Coalition Adoption of Evidence-Informed Strategies initiative, which focuses on community coalitions advancing child health equity.
Methods:
Using the Participatory Implementation Systems Mapping approach, the research team and a five-member Community Advisory Council engaged in a structured, four-stage process to identify system determinants, co-specify implementation strategies and mechanisms, and simulate dynamic behavior. Causal loop diagrams and stock-and-flow diagrams were developed to visualize relationships, inform strategy design, and test expected effects on knowledge, adoption, and coalition decision-making.
Results:
The approach generated over 50 implementation determinants, organized into a coalition-focused conceptual systems framework (Stage 1); causal loop diagrams highlighting key feedback dynamics like knowledge diffusion and positive attitude toward evidence (Stage 2); and stock-and-flow diagrams translating five prioritized strategies into core system variables (Stage 3). Strategies, which included network weaving, informing local leaders, facilitating knowledge exchange, structured evidence review, and decision support tools, were operationalized with specific mechanisms (e.g., communication frequency, network density, perceived appropriateness). Simulations (Stage 4) showed that doubling review frequency increased knowledge by 17% but raised adoption by only 4% without complementary strategies. Adding decision support tools reduced time to reach adoption by 3 weeks, while introducing perceived relative advantage mid-simulation boosted adoption by 22%. Diffusion rates ranged from 0.02 to 0.08/week, moderated by social network quality. DISCUSSION: The study illustrates how systems science methods bridge qualitative insights with quantitative modeling to design and preliminarily test adaptive, contextually relevant implementation strategies. Visualizing feedback loops and representing relationships as stocks and flows provides a framework to assess how implementation strategies influence coalition processes and outcomes. The findings emphasize the importance of participatory processes to ensure strategies are practical and aligned with coalition priorities. Future work should focus on implementation, testing and scaling systems-based approaches to address implementation challenges.
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