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Putting it into Practice

In implementation science, theories, models, and frameworks (TMFs) play crucial roles in guiding research and practice.

Researchers use theories to develop hypotheses, design studies, and evaluate implementation of evidence-based practices. Practitioners can use models to guide their actions during implementation, while frameworks help bridge the gap between research and practice by accounting for real-world complexities.

Theories describe the mechanisms of change—how we create change and help us understand why certain interventions work or fail. By applying theories, researchers and practitioners can design more effective interventions and tailor them to specific contexts.

Process models outline the steps or stages of implementing evidence, providing a roadmap for translating research into practice. Models can enhance consistency and efficiency during implementation.

Frameworks present factors that influence different aspects of implementation and can address complexities beyond the intervention itself. They help us consider context, sustainability, and other critical elements.

Together, theories, models, and frameworks enhance implementation science’s effectiveness and impact. To learn more about TMFs, please visit our page “Theories, Models, & Frameworks.”

Below, you can explore our archive to see examples of five commonly-used TMFs in implementation science, across a range of journals. Open access articles are marked with the ✪ symbol.

The Consolidated Framework for Implementation Research (CFIR) is a widely used conceptual framework that helps researchers and practitioners understand the complex factors influencing the implementation and sustainability of projects. It provides a structure for analyzing contextual elements related to implementation. The CFIR consists of five core domains:

Intervention Characteristics: Examines the features of the intervention being implemented.
Outer Setting: Considers external factors such as the broader environment, policies, and patient needs.
Inner Setting: Focuses on organizational context, culture, and resources.
Implementation Process: Addresses the steps and strategies used during implementation.
Outcomes: Assesses the impact and effectiveness of the implementation effort.

To learn more about the CFIR, please visit our page “Theories, Models, & Frameworks” or visit CFIRGuide.org.

Browse the articles below to see how UW researchers are using the CFIR across contexts.

RE-AIM stands for Reach, Effectiveness, Adoption, Implementation, and Maintenance. It’s a framework designed to guide the planning and evaluation of programs, particularly evidence-based interventions, across various settings and contexts. The five elements of RE-AIM are:

  • Reach: This outcome focuses on the proportion of the target population that participates in the program.
  • Effectiveness: It assesses the impact of the intervention on relevant outcomes.
  • Adoption: This aspect considers how well organizations or individuals adopt and integrate the program.
  • Implementation: It examines the fidelity and quality of program delivery.
  • Maintenance: This outcome looks at the long-term sustainability of the intervention.

RE-AIM helps improve the public health impact of evidence-based interventions by considering these critical dimensions throughout the implementation process. To learn more about the RE-AIM framework, please visit our page “Theories, Models, & Frameworks” or visit re-aim.org.

Browse the articles below to see how UW researchers are using the RE-AIM across contexts.

The Theoretical Domains Framework (TDF) is an integrative framework developed to investigate the determinants of behavior change and design behavior change interventions. It was collaboratively created by behavioral scientists and implementation researchers, who identified relevant theories and grouped their constructs into domains. The TDF provides a comprehensive approach to understanding the factors influencing behavior and helps address implementation challenges. Researchers use it to assess implementation problems, design interventions, and progress from theory-based investigation to practical solutions.

To learn more about the TDF, please visit our page “Theories, Models, & Frameworks.”

Browse the articles below to see how UW researchers are using the TDF across contexts.

The Dynamic Sustainability Framework addresses the challenge of sustaining health interventions amid ongoing change. Rather than assuming diminishing benefits over time, it emphasizes continuous adaptation and improvement. Key components include ongoing learning, problem-solving, and a focus on fit between interventions and multi-level contexts. This framework supports research, policy, and practice to advance the impact of health services research.

Browse the articles below to see how UW researchers are using the Dynamic Sustainability Framework across contexts.

The Exploration, Preparation, Implementation, and Sustainment (EPIS) framework is a comprehensive multiphasic, multi-level implementation model designed to guide implementation research and practice. It provides a structured approach to understanding and addressing the complexities of integrating evidence-based practices (EBPs) into real-world settings. There are four phases of EPIS:

  • Exploration: During this phase, stakeholders consider health needs, identify suitable EBPs, and decide whether to adopt them.
  • Preparation: The focus here is on identifying barriers and facilitators within outer system and inner organizational contexts. Adaptation needs are assessed, and a detailed implementation plan is developed.
  • Implementation: This phase involves putting the EBP into action, considering factors that bridge outer and inner contexts.
  • Sustainment: The goal is to maintain the EBP over time, emphasizing ongoing learning, problem-solving, and fit with the evolving context.

To learn more about EPIS, please visit our page “Theories, Models, & Frameworks or visit EPISframework.com.

Browse the articles below to see how UW researchers are using EPIS across contexts.