This module introduces common methods and study designs used in implementation research. Learners will examine how implementation research balances internal validity, external validity, feasibility, and relevance to real-world decision-making. The module reviews why implementation studies often use multiple methods, including qualitative approaches to explore implementation problems, strengthen measurement, assess fidelity, and interpret why strategies do or do not work. Learners will also review major design options, including observational, experimental, quasi-experimental, mixed-methods, modeling, and Effectiveness–Implementation Hybrid designs. Through applied activities, learners will practice translating an implementation problem into a research question, specific aims, and a feasible study design.

This module introduces theories, models, and frameworks commonly used in implementation science. Learners will distinguish among process models, determinant frameworks, and evaluation frameworks, and consider how each can support different implementation research questions. The module emphasizes practical framework selection: choosing a framework based on the implementation problem, stage, context, and purpose of the study. Learners will also practice using a determinant framework, such as CFIR, to organize and prioritize likely barriers and facilitators for assessment, strategy selection, and later evaluation.

This module focuses on implementation strategies: the actions used to help evidence-based interventions, programs, or policies work in real-world settings. Learners will distinguish implementation strategies from the clinical, public health, or service delivery interventions they are intended to support. The module introduces structured ways to name, specify, and report strategies, including key elements such as actor, action, target, dose, timing, and justification. Learners will also practice using ERIC terminology and determinant-to-strategy logic to build coherent multi-component strategy bundles. The module concludes by considering how strategies can be adapted to local context while preserving their core functions.

This module focuses on how to define and measure implementation success. Learners will distinguish implementation outcomes from clinical effectiveness, service delivery, and health outcomes. The module introduces common implementation outcomes, such as acceptability, adoption, appropriateness, feasibility, fidelity, penetration, cost, and sustainment, and explains how outcome selection should align with the implementation stage, strategy theory of change, and intended use of findings. Learners will also consider pragmatic measurement options, including surveys, administrative data, program records, observation, interviews, and other feasible data sources. The module concludes with basic measurement quality considerations, including reliability, validity, feasibility, relevance, and fit with the implementation context.

This module focuses on study designs used to evaluate implementation strategies in real-world settings. Learners will compare randomized, quasi-experimental, pragmatic, and adaptive approaches, and consider how each design balances feasibility, validity, ethics, and usefulness for decision-making. The module introduces common randomized approaches, such as cluster randomized and stepped-wedge designs, as well as non-randomized approaches used when randomization is not feasible. Learners will also use the pragmatic–explanatory continuum, including tools such as PRECIS-2, to assess how closely a trial reflects real-world conditions. The module concludes with optimization and adaptive designs, such as factorial designs and SMARTs, and asks learners to justify study design choices for evaluating an implementation strategy bundle.

This final module brings together the major concepts covered throughout the course and considers how learners can apply implementation science beyond the course. Learners will revisit the full implementation research pathway: identifying an implementation problem, understanding context and determinants, selecting and specifying implementation strategies, choosing outcomes and measures, and proposing feasible study designs. The module also provides resources for continued learning, including key terms, frameworks, reporting tools, and references that learners can return to as they design, implement, evaluate, or improve real-world programs and services.