| Literature DB >> 19852784 |
Luci K Leykum1, Jacqueline A Pugh, Holly J Lanham, Joel Harmon, Reuben R McDaniel.
Abstract
BACKGROUND: A gap continues to exist between what is known to be effective and what is actually delivered in the usual course of medical care. The goal of implementation research is to reduce this gap. However, a tension exists between the need to obtain generalizeable knowledge through implementation trials, and the inherent differences between healthcare organizations that make standard interventional approaches less likely to succeed. The purpose of this paper is to explore the integration of participatory action research and randomized controlled trial (RCT) study designs to suggest a new approach for studying interventions in healthcare settings. DISCUSSION: We summarize key elements of participatory action research, with particular attention to its collaborative, reflective approach. Elements of participatory action research and RCT study designs are discussed and contrasted, with a complex adaptive systems approach used to frame their integration.Entities:
Year: 2009 PMID: 19852784 PMCID: PMC2770984 DOI: 10.1186/1748-5908-4-69
Source DB: PubMed Journal: Implement Sci ISSN: 1748-5908 Impact factor: 7.327
Essential elements of participatory action research
| [ | |
| [ | |
| [ | |
| [ | |
| [ | |
| [ | |
| [ | |
| [ | |
| [ | |
| [ | |
| [ | |
| [ | |
| [ | |
| [ | |
| [ | |
| [ | |
| [ | |
Elements of PAR, RCT's, and integrated PAR/RCT
| Collaborative design | Externally created, standardized interventions | Key elements of intervention are locally implemented based on collaborative discussion | Use of site PIs in each unique study site as collaborators with study PIs in intervention design |
| Internal control | External control | Joint control | Site PIs with local or shared authority |
| Local applicability | Generalizeable | Use local findings to inform universal understanding | Consider local insights gleaned from the implementation process as data that will form the basis for a general understanding |
| Acknowledge unique local environments | Uniqueness minimized through random assignment | Incorporation of local conditions into overarching approaches | Address local barriers in intervention implementation |
| Reveal biases | Reduce bias | Use bias to form basis of generalizeable understanding | Allowing bias into the design may lead to a better understanding of the implementation process. |
| Reflective process throughout intervention | Endpoints/measurement set in advance | Time function or endpoints may vary within boundaries | Modify endpoints based on results |
| No comparisons, internal focus | Comparisons between arms | Comparisons based on 'content analysis' of internal understandings and lessons | Use of qualitative methods to probe themes from implementation experiences between sites |