Course description
This four-day PhD course provides participants with the opportunity to gain in-depth knowledge of realist methodology as a theory-driven and explanatory approach to studying complex interventions, policies and social programmes, and to develop practical experience in applying its concepts and analytical logic.
The course is aimed at PhD students working with complex interventions, implementation processes, policy evaluation, or evaluation in the health and social sciences. Because realist methodology is not simply a method but an approach with its own philosophical and analytical foundations, the course is organised over four days to provide participants with sufficient time to engage in depth with both its underlying logic and its practical application.
Day 1: Participants will be introduced to the philosophical foundations of realist methodology, including critical realism, generative causation, and retroductive reasoning. Central concepts such as programme theory and CMO-configurations will be introduced and discussed. Through exercises and group-based discussion, participants will work with distinguishing between context, mechanism, and outcome in example cases and critically assessing published realist work.
Day 2: The second day focuses on realist evaluation design and methodological choices. Topics include empirical realist evaluations, realist-informed designs (including introductions to realist trials and realist economic evaluations) and the relationship between research questions, programme theory, data sources, and analytical processes. The day will also address realist interviewing and ripple effects mapping. These topics will be explored through exercises, including discussing design choices in relation to research questions, data sources, and the overall purpose of the study and sketching an initial programme theory.
Day 3: The third day centres on analysis and application. It focuses on analytical strategies within realist evaluation, including retroduction, the development and refinement of CMO configurations, and approaches to theory testing and theory refinement. Participants will work with shared examples as well as their own data and will engage in exercises and discussions aimed at strengthening their ability to move from empirical data to robust explanatory accounts.
Day 4: The final day takes place approximately four weeks later and focuses on practical application and analytical reflection. The interval between the first three days and the fourth follow-up day is intended to give participants time to absorb and reflect on the concepts, principles, and analytical approaches introduced during the course, and to begin working with them in relation to their own material. Before returning, participants will be asked to prepare a small-scale realist analysis in which they formulate at least one tentative CMO-configuration. This may be based on empirical material from their own PhD project or on evidence drawn from scientific literature. The purpose is to gain hands-on experience with realist analytical reasoning. On the final day, participants present their CMO-configurations and receive feedback focusing on conceptual clarity, specification of context and mechanisms, plausibility of causal explanations, and methodological considerations for integrating realist evaluation in their own PhD study.
Intended learning outcome
The course aims to provide participants with a solid working knowledge of realist methodology and its application in the study of interventions, policy and other change programs. Upon completion of the course, participants will have gained an understanding of:
• The philosophical foundations of realist evaluation
• Programme theory and CMO-configurations
• Key differences between realist review, empirical realist evaluation, and realist synthesis
• Realist informed designs, realist trails, and realist economic evaluations
• Realist informed data collection approaches, including realist interviewing and ripple effects mapping
• Reporting standards for realist research
• Core principles of realist analysis
Participants will be able to:
• Explain and critically discuss key concepts and designs in realist evaluation
• Assess the relevance of realist evaluation for their own PhD project
• Apply realist methodology to elicit CMO configurations and build initial program theories
• Critically discuss strengths and limitations of different realist designs and methodological approaches
Teaching methods
Throughout the course, teaching will combine lectures, case examples, group-based exercises, and discussions of participants’ own projects. Practical application and methodological reflection will therefore be integral components across all four days.
Lecturers: Carsten Hinrichsen (SDU) and Charlotte Brøgger Bond (SDU)
Guest lecturers: Stine Dandanell Garn (NFA) (expected workload: 2h lectures, 3h workshop, 2h presence). Through our international network we will invite leading experts within realist methodology to contribute one short online guest lecture and a Q&A session pr. course (e.g. Kev Harris Hartpury University and Hartpury College, UK)(expected workload: 1h lecture, 1h workshop).
NB: For the first time the course is offered, we propose having two lecturers present, reflecting the collaborative and cross-departmental development of the course (although this is not a requirement). This is the basis for the stated number of workload below. In subsequent iterations of the course, the number of lecturers present may be reduced. Staffing for workshop components will depend on the number of participants (numbers below are based on expected no of participants)
The course is taught by Carsten Hinrichsen and Charlotte Brøgger Bond (SDU), with contributions from Stine Dandanell Garn (Capital Region of Denmark) and an online guest session with Ana Manzano (University of Leeds).
Course Fee
The course is free of charge for PhD students enrolled in Universities that have joined the Open market agreement and NorDoc.
For other participants there is a course fee of:
DKK 4700
EUR 628