Yöntem Karşılaştırma

	Process Evaluation	Realist Evaluation
Alan	Public Policy	Public Policy
Aile	Process / pipeline	Process / pipeline
Köken yılı	2015	1997
Köken	Health-promotion & MRC evaluation tradition (Saunders et al.; Moore et al.)	Ray Pawson & Nick Tilley
Tür	Implementation-focused program evaluation	Theory-driven, generative evaluation approach
Seminal kaynak	Moore, G. F., Audrey, S., Barker, M., Bond, L., Bonell, C., Hardeman, W., et al. (2015). Process evaluation of complex interventions: Medical Research Council guidance. BMJ, 350, h1258.	Pawson, R., & Tilley, N. (1997). Realistic Evaluation. London: SAGE Publications. ISBN: 9780761950097
Diğer adlar	Implementation Evaluation, Implementation Fidelity Evaluation, Program Process Evaluation	Realistic Evaluation, Theory-Driven Realist Evaluation, CMO Configuration Analysis, Pawson-Tilley Evaluation
İlişkili	3	4
Özet	Process evaluation examines how a program or policy was actually implemented, rather than only whether it achieved its outcomes. It documents what was delivered, to whom, how much, how well and in what context, so that outcome findings can be interpreted correctly. By assessing implementation fidelity, dose, reach, and the mechanisms and contextual factors at work, process evaluation explains why an intervention succeeded or failed and distinguishes a flawed program theory from a sound theory that was poorly delivered. The UK Medical Research Council's 2015 guidance and earlier health-promotion frameworks consolidated it as a core component of evaluating complex interventions.	Realist evaluation is a theory-driven approach to evaluating programs and policies that asks not simply 'does it work?' but 'what works, for whom, in what circumstances, and why?'. Developed by Ray Pawson and Nick Tilley in their 1997 book Realistic Evaluation, it treats interventions as theories incarnate: programs offer resources or opportunities that trigger underlying mechanisms of reasoning and response in participants, and those mechanisms only fire in particular contexts. The unit of analysis is the Context-Mechanism-Outcome (CMO) configuration, and the goal is to build and refine middle-range theory that explains differential outcomes across settings.