A framework for strengthening realist synthesis and evaluation by integrating behavioural science
Justin Aunger & Robert Aunger
Abstract
Understanding the mechanisms and contexts that drive the success of complex health interventions remains a challenge. Realist methods, grounded in scientific realism, generate context-sensitive programme theories to explain how, why and for whom interventions work, but these theories often lack structured operationalisation to inform comparison or intervention design. Behavioural science, by contrast, systematically identifies and modifies behaviour change mechanisms using theory-driven frameworks, but has been criticised for insufficiently considering context. Integrating these may enhance the precision, standardisation and applicability of realist programme theories. This novel approach leverages behavioural science concepts such as behaviour change techniques and mechanisms of action to clarify mechanisms, and uses the idea of behavioural settings to explicate context. Together, this establishes a common language for programme theory formulation, making them more structured, testable and transferable. A five-step framework for integration is proposed for realist studies, facilitating more precise and transferable theories that support intervention design and policy translation.
Evidence weight
Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40
| F · citation impact | 0.50 × 0.4 = 0.20 |
| M · momentum | 0.50 × 0.15 = 0.07 |
| V · venue signal | 0.50 × 0.05 = 0.03 |
| R · text relevance † | 0.50 × 0.4 = 0.20 |
† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.