A case study of integrated knowledge translation in the context of en masse interinstitutional relocation of a long-term care home in Canada

Author: 
Date created: 
2019-09-27
Identifier: 
etd20431
Keywords: 
Knowledge translation
Integrated knowledge translation
Knowledge to Action model
Deliberative dialogues
En masse interinstitutional relocations
Long-term care
Abstract: 

The knowledge translation (KT) literature continues to grow but a gap persists in our understanding of the utility and application of the numerous KT models due to limited reporting and analysis in the literature. To address this gap, a case study of an integrated KT (iKT) project that applied the Knowledge to Action (KtoA) model (Graham et al., 2006) in the development of a guiding framework to support en masse interinstitutional relocations of long-term care (LTC) homes was completed. Specifically, the research questions were 1) what was the relevance and utility of applying the KtoA model to an iKT project, and 2) what approaches used provided new insight and how could that be applied to other projects? Central to KT is knowledge synthesis and central to iKT is stakeholder engagement, the evidence and processes used detailed in this case study include: in-depth interviews with residents, staff and families; World Café dialogues with experienced LTC informants; and a research literature synthesis. The use of the KtoA model and its limitations are explored, including the lack of emphasis on relationality and context within the model. In addition, the challenges and lessons learned with the World Café approach to deliberative dialogues are explored including the pitfalls of biased method selection and the richness of interactive conversations. The findings of this case study contributes to the KT literature through the detailed reporting and analysis of the use of the KtoA model and engagement methods that can inform further KT model and methods development.

Document type: 
Thesis
Rights: 
This thesis may be printed or downloaded for non-commercial research and scholarly purposes. Copyright remains with the author.
Senior supervisor: 
Marina Morrow
Department: 
Health Sciences: Faculty of Health Sciences
Thesis type: 
(Thesis) Ph.D.
Statistics: