Building a Logic Model to Foster Engagement and Learning Using the Case of a Province-Wide Multispecies Antimicrobial Use Monitoring System

Successfully designing and implementing a program is complex; it requires a reflexive balance between the available resources and the priorities of various stakeholders, both of which change over time. Logic models are theory-based evaluation approaches used to identify and address key challenges of a program. This article describes the process of building a logic model on advanced theories in complexity studies. The models aim to support a province-wide multispecies monitoring system of antimicrobial use (AMU), designed in collaboration with the animal health sector in Quebec (Canada). Based on a rigorous theoretical foundation, the logic model is built in three steps: (1) mapping , a narrative review of literature on similar programs in other jurisdictions; (2) framing, iterative consultations with project members to elaborate the logic model; (3) shaping , hypotheses based on the logic model. The model emerges from the reflexive balancing of current scientific knowledge and empirical insights to gather relevant information about stakeholders from interdisciplinary experts that led a 3-year consensus-building process within the community. Recognizing the challenge of unpacking theories for practical use, we illustrate how the process of an “open†logic model building could enable governance coordination in complex processes. Logic models are useful for evaluating public, private, and academic partnerships in One Health programs that characterize an adaptive governance process.