Objective(s): The present study was aimed to design a KNOWLEDGE transfer MODEL that would provide a conceptual framework for linking the different components of a KNOWLEDGE TRANSLATION cycle. Such a theoretical MODEL will enable us to organize and evaluate the current situation and design further studies on the transfer of research generated KNOWLEDGE. Methods: This research, performed in 2006-7 in Tehran University of Medical Sciences, utilized two distinct methodologies: the first part was a narrative review with the goal of identifying the existing KNOWLEDGE transfer MODELs; the second part included focus group discussions to find out the views and opinions of researchers and decision-makers concerning the factors that promote or hinder KNOWLEDGE TRANSLATION within the health system. Results: The two studies have provided the input for designing a “KNOWLEDGE TRANSLATION Cycle” with five domains: KNOWLEDGE Creation, KNOWLEDGE Transfer, Research Utilization, Question Transfer, and the Context of University. Within each domain, the MODEL includes two components (with the exception of the university context). Conclusion: This MODEL offers a theoretical basis for identifying the basic requirements and the linking mechanisms for the TRANSLATION of KNOWLEDGE.

Objective(s): The main purpose of the study was the development of a self-assessment tool for research organizations to enable them to assess KNOWLEDGE TRANSLATION in their own settings. Methods: The development of this self-assessment tool is done based on a narrative review and subsequent focus group discussions, to design a KNOWLEDGE TRANSLATION MODEL that would provide a conceptual framework for linking the different components of a KNOWLEDGE TRANSLATION cycle, which reported previously. Repeatability of the self-assessment domains was assessed in the 21 participants using intraclass correlation coefficient (ICC). Each participant filled the form twice within a two-week interval. The internal consistency for each domain was estimated in the 45 study subjects using Cronbach’s alpha. Results: This self-assessment tool is an instrument that allows stakeholders in a research organization to review their own KNOWLEDGE TRANSLATION activities. This tool consists of 50 statements in four domains; 1- The research question, 2- KNOWLEDGE production, 3- KNOWLEDGE transfer and 4- Promoting the use of evidence. The respective ICCs and Cronbach’s alpha for the four domains were 0.94 and 0.79 for the research question, 0.87 and 0.70 for KNOWLEDGE production, 0.90 and 0.86 for KNOWLEDGE transfer, 0.48 and 0.27 for promoting the use of evidence. Conclusion: This self-assessment tool is a way of listing the wide range of variables that affect KNOWLEDGE TRANSLATION at organizational level. Although the tool is intended for use by a group of people and not by individuals, it is not a survey instrument and its results should not be interpreted quantitatively. Therefore, this self-assessment tool can be useful for assessing the KNOWLEDGE TRANSLATION activities of each research organization, thereby identifying its shortcomings and seeking ways to improve them.

This commentary examines the claim made by Borst et al that KNOWLEDGE TRANSLATION (KT) should look to Science and Technology Studies (STS), the sociology of TRANSLATION, and constructionist views on KNOWLEDGE, and begin to think of the sustainability of a certain practice as construction work in continuous progress, and not as states to be reached once and for all. While endorsing this claim, the present commentary also argues that what it calls the “epistemic reframing” behind the new construal of KT in Borst must be supplemented with approaches that goes beyond the sociology of TRANSLATION. The commentary claims that this epistemic shift hinges upon a shift in the narrative framing of KT, and that we need to consider the broader narrative and historical ideology of KNOWLEDGE dissemination behind KT, and that a failure to do so, leaves us with KT seen as a linear transmission of “true” KNOWLEDGE to peoples and places lacking such KNOWLEDGE.

KNOWLEDGE TRANSLATION was created in response to the KNOWLEDGE-do gap. With the growing number of research projects, utilization of research KNOWLEDGE roused interest. One of its defects, which are seen more in developing countries, is the scarcity of recognized practical KNOWLEDGE TRANSLATION applications. The actions taken to strengthen KNOWLEDGE TRANSLATION can be classified into three categories of ‘push, pull and exchange’. In Iran, some of the interventions effective in KNOWLEDGE TRANSLATION, may not have primarily taken place with this aim, but can however be effective in it. Some of the measures taken specifically in Iran’s research system are: capacity building of human resources for KNOWLEDGE TRANSLATION, better utilization of research by the Ministry of Health and Medical Education, creating necessary incentives among medical universities, identification of barriers and proposing interventions. Pilots of KNOWLEDGE TRANSLATION interventions are concerned with ‘push’ activities whose main focus is to support KNOWLEDGE TRANSLATION activities and promote active strategies (or increase interaction between researchers and decision makers during research and utilization of results). Long-plan programs such as ‘Iran’s Health Innovation and Science Development plan have also been designed for the future. These include formation of centers for reducing the KNOWLEDGE-do gap in the form of KNOWLEDGE and health technology TRANSLATION centers.

KNOWLEDGE TRANSLATION (KT) is the meeting ground between two fundamentally different processes: research and action. It knits them with communicative relationships. KNOWLEDGE TRANSLATION is a dynamic and interactive process that includes synthesis, dissemination, exchange and ethically sound application of KNOWLEDGE to provide more effective services and products and strengthen system. This is done through a complex system of researchers and KNOWLEDGE users. KNOWLEDGE TRANSLATION is catalyst for KNOWLEDGE cycle in KNOWLEDGE to action process. Utilization of observation and decision-making appropriate with field conditions that is proposed with KNOWLEDGE TRANSLATION is very useful in industrial researches. This research proposes a MODEL for KNOWLEDGE TRANSLATION from research to industry (case study: A Defense Industry Research Center). By extending the concept of KNOWLEDGE TRANSLATION several MODELs and structures are proposed that each one has a strategy to overcome the gap between what we know and what actually happens in practice. In this research we studied some of them and try to find an appropriate MODEL. The proposed MODEL has seven processes: research needs assessment, input to research, research processes, primary outputs from research, making a sample for taking customers endorsement, using product and final outcome. For data collection, interviews and questionnaires were used. The population is consisting of experts, managers and Defensive Research Centers researchers who are familiar with KNOWLEDGE TRANSLATION issues.

The critical interpretive synthesis by Borst and colleagues offered a new perspective on KNOWLEDGE TRANSLATION (KT) sustainability from the perspective of Science and Technology Studies. From our applied health services perspective, we found several interesting ideas to bring forward. First, the idea that KT sustainability includes the ongoing activation of networks led to several future research questions. Second, while not entirely a new concept, understanding how KT actors work strategically and continuously with institutional rules and regulations to sustain KT practice was noteworthy. We add to the discussion by emphasizing the importance of non-researcher voices (clinicians, administrators, policy-makers, patients, carers, public) in sustaining KT practice. We also remind readers that the health ecosystem is dynamic and interdependent, where one system level influences and is influenced by another, and that these constant adaptations suggest that understanding KT practices cannot be a one-off event but represent repeated moments for transformative learning.

Putting health theories, research and KNOWLEDGE into practice is a challenge referred to as the KNOWLEDGE-to-action gap. KNOWLEDGE TRANSLATION (KT), and its related concepts of KNOWLEDGE mobilization, implementation science and research impact, emerged to mitigate this gap. While the social interaction view of KT has gained currency, scholars have not easily made a link between KT and the concept of complexity. Kitson and colleagues suggest we ought to examine the role of complexity in KT processes using defined theories and concepts borrowed from network and complex adaptive systems theory. They further argue that better KT outcomes might be achieved using this new lens. There remain, however, several critical considerations for this sort of theory application to work in the real-world. Complexity and network theory offer explanatory power about the KT problem, but these theories are less helpful for understanding solutions.