Centre for Advancement in Realist Evaluation and Synthesis (CARES)

Video: Introduction to Realist Evaluation and Synthesis

Dr. Justin Jagosh introduces foundational concepts in Realist Methodology in an interactive seminar through Engage@Liverpool, January 25th, 2017.

Welcome to the website for the Centre for Advancement in Realist Evaluation and Synthesis (CARES), operated by Dr. Justin Jagosh. Realist methodology (in the tradition of Pawson and Tilley 1997; Pawson 2006, 2013) is a theory-driven approach to understanding 'what works, for whom, under what circumstances and how' for programmes, services, interventions and policies. The methodology is burgeoning for assessment across many sectors including health and social service, crime prevention, social policy, international development and environmental studies. For an introduction to the methodology, please feel free to view this video


Pawson R, & Tilley N. (1997). Realistic Evaluation. Thousand Oaks, CA: Sage.

Pawson R, (2006). Evidence-Based Policy: A Realist perspective, Thousand Oaks, CA: Sage

Pawson R, (2013). The Science of Evaluation: A Realist Manifesto, Thousand Oaks, CA: Sage

Evidencing Generative Causal Pathways: Future Directions in Realist Inquiry
Delivered for: Realist Approaches Workshop - Founding Principles and Contemporary Developments, Northumbria University, (UK)
November 14th, 2018

Many programmes have lofty outcome goals for addressing entrenched and complex problems. The way in which generative causal pathways (and rival pathways) are envisioned will shape ideas about evaluation design. Programmes are often implemented with the hope for resolution of acute problems. In these instances, an absence of vision of the potential longer-term ripple effects can result in a blindness to potential harms and complications attributable to such programmes.


The Importance of Understanding Context
Delivered for the School of Public Health, University of Queensland, Australia on February 13th, 2018.

Realist inquiry uses programme and middle-range theory and context-mechanism-outcome configuration to address the questions, 'what works, for whom, under what circumstances and how?' This approach to research and evaluation can be adapted in many ways – including in the design of large-scale study, literature-based knowledge synthesis, policy appraisal, implementation scale-up, and in day-to-day decision-making. In this introductory webinar, ideas from Realist Evaluation will be presented to clarify why it is important to understand context.


The Context + Mechanism Association:
A Key Heuristic in Realist Evaluation for Innovating Programmes
Delivered for the Centre for Complexity Across the Nexus (CECAN)
June 26th, 2017

Undertaking inquiry using the realist approach involves analysing complexity in terms of context-mechanism-outcome configurations. Confusion often arises in determining when data should fit under 'context' or else 'mechanism' in the process of configuring.This webinar will offer a simple set of definitions for context, mechanism and outcome to clarify this issue and will introduce examples of CMO configuring to demonstrate the context-mechanism interaction.The goal is to stimulate ideas around how to define concepts, theorize programmes and configure data in realist analysis, with the ultimate ambition of increasing capacity for using realist evaluation to innovate and transform programmes.    


Dosage, Timelines, and other Important Considerations for Realist Evaluation:    
Delivered for the Centre for Complexity Across the Nexus (CECAN)
September 6th, 2017

The functioning of a programme can be determined from the realist theories that sketch out its basic architecture. This becomes increasingly evident in the process of theory testing using the context-mechanism-outcome configuration in which we try to understand how resources, when placed in environments trigger responses to produce outcomes.In understanding how programmes work, we may arrive at questions about dosage (e.g., how many times should we expect the resource to be delivered before the desired response will be triggered?) and timelines of impact (e.g., what are reasonable estimations of time delay between the introduction of resources and the triggering of response?). Using examples, this webinar will demonstrate why dosage and timelines of impact are important considerations in the process of realist theory developing and testing.