Realist Evaluation
Realist evaluation is a theory-driven approach that seeks to understand how and why interventions work (or don't) in specific contexts by identifying the underlying causal mechanisms at play. It helps to develop context-mechanism-outcome (CMO) statements, providing a nuanced understanding of program effectiveness.
Use realist evaluation when you need to understand the complexities of a program, especially when implemented across multiple settings, and when you want to learn how to adapt interventions to suit specific contexts for scaling up or rolling out.
Solves: Lack of understanding of why a program works in some contexts but not others; difficulty in adapting programs to new settings; superficial evaluation findings that don't provide actionable insights.
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Step 1: Develop an initial program theory based on existing knowledge, research, and assumptions about how the intervention is expected to work. (60 min)
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Step 2: Collect data (qualitative and quantitative) to test the different elements of the program theory, focusing on context, mechanisms, and outcomes. (Variable)
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Step 3: Analyze the data to identify patterns and develop CMO configurations that explain the observed outcomes. (120 min)
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Step 4: Refine the program theory based on the evaluation findings, modifying it to reflect the complexities of the intervention and its context. (60 min)
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Step 5: Disseminate the findings and use them to inform decision-making about program adaptation and scaling. (30 min)
- Ensure that the initial program theory is well-defined and testable.
- Use a mix of qualitative and quantitative data to provide a comprehensive understanding of the intervention.
- Involve stakeholders in the evaluation process to ensure that the findings are relevant and useful.
- Focus on specific aspects of the program theory.
- Use different data collection methods.
- Involve different stakeholders in the evaluation process.