Introduction: The use of restrictive practices has significant adverse effects on the individual, care providers and organisations. This review will describe how, why, for whom, and in what circumstances approaches used by healthcare organisations work to prevent and reduce the use of restrictive practices on adults with learning disabilities. Methods and analysis: Evidence from the literature will be synthesised using a realist review approach - an interpretative, theory-driven approach to understand how complex healthcare approaches work in reducing the use of restrictive practices in these settings. In step 1, existing theories will be located to explore what approaches work by consulting with key topic experts, holding consultation workshops with healthcare professionals, academics, and experts by experience, and performing an informal search to help develop an initial programme theory. A systematic search will be performed in the second step in electronic databases. Further searches will be performed iteratively to test particular subcomponents of the initial programme theory, which will also include the use of the CLUSTER approach. Evidence judged as relevant and rigorous will be used to test the initial programme theory. In step three, data will be extracted and coded inductively and deductively. The final step will involve using a realist logic of analysis to refine the initial programme theory in light of evidence. This will then provide a basis to describe and explain what key approaches work, why, how and in what circumstances in preventing and reducing the use of restrictive practices in adults with learning disabilities in healthcare settings. Results: Findings will be used to provide recommendations for practice and policymaking. Registration: In accordance with the guidelines, this realist review protocol was registered with the International Prospective Register of Systematic Reviews (PROSPERO) on 4th December 2019 (CRD42019158432).
- Study Protocol
- Biology and life sciences
- Research and analysis methods
- Medicine and health sciences
- Social sciences
- Computer and information sciences