Using implementation science theories and frameworks in global health.

Area of Science:

• Global Health
• Implementation Science
• Health Policy Evaluation

Background:

• Growing interest in evaluating global health interventions among researchers and decision-makers.
• Implementation science, with roots in the 1930s, provides robust theories and frameworks for research quality.
• Existing quantitative backgrounds in global health may lack familiarity with implementation science methodologies.

Purpose of the Study:

• To introduce researchers and decision-makers to the theories and analytic frameworks of implementation science.
• To define four models of causation: intervention theory, frameworks, middle-range theory, and grand theory.
• To explain the application of these models in three core implementation studies: fidelity assessment, process evaluation, and complex evaluation.

Main Methods:

• Defining and explaining four models of causation in implementation science.
• Illustrating the application of these models through three types of implementation studies.
• Providing concrete examples from global health research in Cuba and Africa.

Main Results:

• The article defines key theoretical models and analytic frameworks within implementation science.
• It demonstrates practical applications of these models in fidelity assessment, process evaluation, and complex evaluation.
• Case examples from Cuba and Africa illustrate real-world implementation challenges and solutions.

Conclusions:

• Researchers and decision-makers will gain awareness of rigorous implementation evaluation needs.
• The study emphasizes the importance of implementation evaluations alongside impact evaluations in global health.
• Collaboration with social scientists is highlighted as crucial for effective global health intervention implementation.