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The Implementation Research Logic Model: a method for planning, executing, reporting, and synthesizing implementation

Justin D Smith1,2, Dennis H Li3, Miriam R Rafferty4

  • 1Department of Population Health Sciences, University of Utah School of Medicine, Salt Lake City, Utah, USA. jd.smith@hsc.utah.edu.

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|September 29, 2020
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Summary
This summary is machine-generated.

The Implementation Research Logic Model (IRLM) provides a structured tool to clarify complex implementation research projects. It enhances the rigor and transparency of linking determinants, strategies, and outcomes for better evidence-based intervention adoption.

Keywords:
IntegrationLogic modelsProgram theoryStudy specification

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Area of Science:

  • Health Services Research
  • Implementation Science
  • Translational Science

Background:

  • Existing implementation research models often lack clear rationale for linking project components.
  • A need exists for tools to specify conceptual linkages between determinants, strategies, and outcomes in implementation research.
  • The Implementation Research Logic Model (IRLM) was developed to address these gaps.

Purpose of the Study:

  • To introduce the Implementation Research Logic Model (IRLM) as a tool to enhance rigor and transparency in implementation research.
  • To provide a method for clearly specifying and testing the causal pathways in implementation research projects.
  • To aid researchers and partners in planning and executing practice change initiatives.

Main Methods:

  • The IRLM was developed through preliminary activities with diverse implementation research projects.
  • Guiding principles and variations for common designs were established.
  • Utility was evaluated via a 2-day training for over 130 implementation researchers and healthcare partners.

Main Results:

  • The IRLM offers a core structure and variations for various implementation research scenarios.
  • Evaluation indicated high utility for improving project rigor, reproducibility, and clarity.
  • The IRLM serves as a roadmap for understanding connections between determinants, strategies, mechanisms, and outcomes.

Conclusions:

  • The IRLM is a principle-guided tool enhancing specification, rigor, and reproducibility in implementation research.
  • It facilitates understanding of testable causal pathways and aids in planning practice change.
  • Ongoing adaptation and resource development aim to support diverse applications in this complex field.