The need for retroductive thinking in implementation sciences

Abstract Background Evidence informing the practice of healthcare and health-related policymaking is predominantly obtained via deduction and induction. While the evidence obtained through these forms of reasoning, mostly from methodologically sound and controlled research environments, are in most part considered robust, they are usually decontextualized, making their adoption and implementation in open systems challenging. We illustrate how the use of retroduction in theoretically-informative empirical research provides evidence linked to the contextual features of its discovery, thus, enhancing learning and implementation. Methods Using a critical realist-informed evaluation study, we illustrate the application of retroductive thinking as a theoretically informative inferencing approach to develop mechanism-based causality context-linked explanatory theories. We expatiate on the application of counterfactual thinking, abductive reasoning and extreme case selection as valuable tools to enhance retroductive thinking. Results The application of counterfactual thinking, abductive reasoning and extreme case selection as tools of retroductive thinking are conceptualized to demonstrate how studies using retroduction can obtain context-linked evidence that can facilitate learning and implementation. Conclusion Obtaining evidence with discovery context provides practical knowledge for implementers to make contextual judgments about what is likely to work in under what likely contextual conditions, for what section of the population. The transcendental philosophical foundation of critical realism makes it favorable for obtaining context-linked explanatory theories through retroduction.