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Methods in realist evaluation: A mapping review.

Dimitri Renmans1, Virginia Castellano Pleguezuelo2

  • 1Ecole de Santé Publique, Université Libre de Bruxelles, Route du Lennik 808, 1070 Brussels, Belgium; Institute of Development Policy (IOB), University of Antwerp, Lange Sint-Annastraat 7, 2000 Antwerp, Belgium.

Evaluation and Program Planning
|December 26, 2022
PubMed
Summary
This summary is machine-generated.

Realist evaluation explains intervention outcomes by examining mechanisms and context. This review found qualitative methods are common but theory and innovative approaches are underused, suggesting improvements for stronger evaluation practices.

Keywords:
Data collection methodsInterviewObservationRealist evaluationSurveysTheory-driven evaluation

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Area of Science:

  • Social Sciences
  • Evaluation Methodology

Background:

  • Realist evaluation is a popular methodology focused on understanding intervention mechanisms and contextual conditions.
  • It aims to explain why, for whom, and under what circumstances interventions are effective.
  • This approach is theory-driven and method-neutral, allowing for diverse data collection techniques.

Approach:

  • This review maps the methods employed in realist evaluation studies.
  • It analyzes findings to draw lessons and propose future directions.
  • The study identifies common practices and areas for development in realist evaluation.

Key Points:

  • Qualitative methods, particularly interviews, are most frequently used in realist evaluations.
  • Theory is often insufficiently integrated with the methods and sampling strategies.
  • Innovative data collection methods are underexplored in current realist evaluation research.

Conclusions:

  • Four key areas for advancement are proposed: developing realist surveys, exploring innovative methods, enhancing attention to sampling procedures, and strengthening the theory-driven nature of methods.
  • Implementing these action points can significantly improve the practice and outcomes of realist evaluation.
  • Strengthening the theoretical underpinnings and methodological diversity can enhance the explanatory power of realist evaluations.