Development of a 'real-world' logic model through testing the feasibility of a complex healthcare intervention: the challenge of reconciling scalability and context-sensitivity. (January 2022)

• Record Type: Journal Article
• Authors: Mills, Thomas; Shannon, Rosie; O'Hara, Jane; Lawton, Rebecca; Sheard, Laura
• Is Part Of: Evaluation. Volume 28:Number 1(2022)
• Page Start: 113
• Page End: 131
• Publication Date: 2022-01
• Subjects: complex intervention -- complexity science -- context -- health services research -- implementation science -- logic model; Evaluation research (Social action programs) -- Periodicals; 361.61068
• DOI: 10.1177/13563890211068869
• Languages: English
• ISSNs: 1356-3890

Abstract

Logic models feature prominently in intervention research yet there is increasing debate about their ability to express how interventions work in the real-world. 'Real-world' logic models are a new proposition which express complex interventions in context. They are designed to help researchers strike a balance between context-sensitivity and scalability. This article explores the utility of real-world logic models in a trial involving a complex intervention called 'Your Care Needs You', designed to improve hospital-home transitions for UK older patients. The approach is found to usefully capture, refine and express important learning about intervention-implementation-context dynamics. The findings imply the need for intervention researchers to think creatively about how to implement interventions in diverse and sometimes challenging environments and to develop understanding of how complex interventions adapt on implementation to produce outcomes. The possibility of assessing the wider social and policy context within intervention research is also posed.