Unpacking Core Components for Policy Design: A comparison of Synthesis Approaches
Article
Summaries of studies on an intervention traditionally have focused on the entire intervention as a way to inform policy. But now researchers are studying elements of an intervention—core components--to see which ones contribute to its success. Understanding core components enables policymakers to identify with greater precision what works, in which contexts, and for which populations.
To advance core components analysis for policy design, this Research Note describes and compares four synthesis approaches for identifying core components in the context of evidence reviews:
- the distillation and matching model, which codes interventions according to their common components (distilling) and then examines their co-occurrence (matching) across target groups, settings, or other factors that might be relevant considerations for selecting an intervention
- meta-regression, which characterizes the relationship between cause and effect in probabilistic terms
- framework synthesis, which draws causal conclusions from observations of the repeated occurrence of the same cause followed by the same effect
- qualitative comparative analysis, which identifies causal conditions, such as intervention components or contextual conditions, that individually or in specified configurations generate an outcome of interest.
The article recommends ways to advance core components analysis to inform policy design and the policy-making process:
- Include more detailed reporting of the intervention characteristics, setting, participants, implementation, and costs in primary studies of interventions
- Use multi-phased designs to generate stronger evidence, with the first phase including core component analyses of the evidence and the second phase including design and implementation of field trials to evaluate the effectiveness of the preliminary set of identified core components
- Apply core components analysis across a broader range of interventions, practices, and policies, with diverse populations and settings.
Extending evidence reviews with one or more of these approaches holds potential to improve policy design and practice. Promoting core components analysis across diverse substantive policy areas can help policymakers design more effective policies for different populations and contexts.