The PARiHS framework (Promoting Action on Research Implementation in Health Services) has proved to be a useful practical and conceptual heuristic for many researchers and practitioners in framing their research or knowledge translation endeavours. However, as a conceptual framework it still remains untested and therefore its contribution to the overall development and testing of theory in the field of implementation science is largely unquantified.
Elements Of Translation : A Prac
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Secondly, the paper describes the next phase of our work, in particular concentrating on the conceptual thinking and mapping that has led to the generation of the hypothesis that the PARiHS framework is best utilised as a two-stage process: as a preliminary (diagnostic and evaluative) measure of the elements and sub-elements of evidence (E) and context (C), and then using the aggregated data from these measures to determine the most appropriate facilitation method. The exact nature of the intervention is thus determined by the specific actors in the specific context at a specific time and place.
In the process of refining this next phase of our work, we have had to consider the wider issues around the use of theories to inform and shape our research activity; the ongoing challenges of developing robust and sensitive measures; facilitation as an intervention for getting research into practice; and finally to note how the current debates around evidence into practice are adopting wider notions that fit innovations more generally.
The spread of best practice and the use of best evidence remain sporadic. There continues to be a tension between policy imperatives and the ability to successfully support and enable local developments. Arguably the debate about how to implement evidence effectively reflects a lack of a true appreciation or understanding of the multiple factors involved. However, there has been a shift away from the traditional notion that getting evidence into practice is straightforward. Until relatively recently the spread of evidence was seen as a linear and technical process at the level of the individual, and was described as changes in clinicians' behaviour in line with evidence-based guidelines [1]. Now there is widespread recognition that guideline implementation, and evidence implementation more generally, requires whole system change implicating both the individual and organisation ([2, 3]). Despite a growing awareness that getting evidence into practice is a complex, multi-faceted process, there remains a lack of knowledge about what methods and approaches are effective, with whom and in what contexts.
Melding and implementing such evidence in practice involves negotiation and developing a shared understanding about the benefits, disbenefits, risks, and advantages of the new over the old. This is a dialectical process that requires careful management and choreography, and one that is not done in isolation; in other words, it is a team effort.
The objective of the current phase of our work is to build on the concept analysis and clarification undertaken in phases one and two, and to evaluate the current framework through the development and testing of diagnostic and evaluative instruments to assist in the process of knowledge translation. Whilst conducting this phase, a number of challenges have arisen, which, whilst reflecting the particular complexities of the PARiHS framework's development, are also relevant to current debates in the field of knowledge translation. These include:
Engaging in the challenges measurement presents and particularly within a theoretical position which argues that the intervention (a precise and tailor-made type of facilitation constructed by a skilled facilitator and those involved in the implementation process) is contingent upon the diagnosis of the evidence and context elements and clarifying facilitation as an intervention.
In contrast, Graham et al. have offered their own conceptual framework to help elucidate what they believe to be the key elements of the knowledge-to-action process [15]. Essentially the framework is divided into two elements or concepts: knowledge creation and action, with specific steps within each element. (For a detailed explanation see Graham et al. [15].) The framework also begins to articulate the embedded theoretical positions that determine action. Graham and colleagues are particularly interested in theories of planned action [19] and have identified over 60 theories or frameworks (although the authors do not distinguish between these terms in their paper).
Therefore, one important question is whether it matters what we call these mental devices. Is there a difference between conceptual frameworks, theories, and models, and, if so, what and how would such differentiations help our understanding of the complex world of research implementation or knowledge translation? Identical questions have been posed in the discipline of public policy analysis and implementation, as well as theory development [29]. The policy world is complex, with multiple elements interacting over time. How can complex situations be simplified in order to understand them, and how can the tension be managed between the exploration of specific interventions within a system and the overall appreciation of the impact of the intervention on the whole system? In attempting to create a deeper understanding, Sabatier and colleagues have described three dominant approaches to policy analysis and implementation [29]. Within this analytic framework they have also put forward a typology for understanding the different 'mental representations' we could use to hold onto the complex world. This analytic framework, first proposed by Ostrom [30, 31], has been used as a way of trying to make sense of the different ways that frameworks, theories, and models could be used to inform our research activity. Ostrom [31] argued that:
How does this analysis help to guide users in successfully implementing evidence into practice? We could use the analogy that the PARiHS framework is like a chess game. There is a defined set of rules and an agreed number of chess players. The pawns, knights, king, queen, bishops, etc. each have a set of rules to follow. Each chess piece has its own provenance or theoretical background that would explain the reason why different pieces move in certain ways. Equally, in each game the unique configuration of the chess pieces creates an almost infinite number of moves that can test the boundaries of movement of each piece, and equally test the boundaries of the higher rules of the game (framework) itself. Each new game could be like a model that will test the theories of the chess pieces within the boundaries of the chess game, i.e. the conceptual framework.
However, unlike the chess game, we still do not know the rules (should there be any) of the knowledge translation game and the movements of the different pieces are yet to be fully understood. Of course, this analogy only works if we accept the prior assumption that implementation processes are predictable, and that there are certain causes and effects at work. The converse position is to assume that all interactions are random, and that there is no predictive capacity because of the complexity involved in working with so many variables. Given that we do not know which of these positions is the more accurate, and it is largely dependent on one's world view of how these issues should be studied, we argue that it is legitimate to proceed with the "chess game analogy" until there is sufficient evidence amassed to disprove it. Taking such an a priori position is consistent to Kuhn's notion that all good scientific endeavours are about the business of empirically falsifying propositions within a theoretical framework [29].
Thus, to conceptualise the process of introducing evidence into practice, we are suggesting that to use the PARiHS framework, practitioners and researchers contemplate the interplay of evidence, context, and facilitation, as well as their sub-elements. Each element and sub-element has a conceptual and theoretical order that determines its intrinsic properties; the interaction of these elements is conditional on their state, maturity, context, and many other factors. The modelling or experimentation that can be constructed is a way of tracking the nature of the different elements and beginning to map the processes by which change occurs through the interaction of these elements.
Table 2 illustrates how the PARiHS framework elements (evidence, context and facilitation) could draw on multiple theoretical perspectives. This, in turn, offers even more models that can then be used to explore systematically the consequences of these propositions in a clearly defined and controlled set of outcomes. What begins to emerge when looking at Table 2 is that, depending on the theoretical approach taken, there is any number of entry points into testing elements of the framework.
How researchers and practitioners "make sense" of the bigger conceptual framework is a fundamental question and an on-going challenge reflecting the complexities involved. The choice of theoretical perspective will necessarily put a boundary around the area of investigation. For example, if we want to investigate the impact of opinion leaders on research implementation using transformational leadership theory, then we will still be left with the job of integrating these findings into the bigger conceptual picture of how research findings get into practice. Holding one piece of the conceptual jigsaw without negating the possible impact of other factors is very important but very difficult to manage. The proposed links are hypothetical and illustrate the conceptual challenges of any nascent discipline.
Such an approach to framework and theory use and development requires researchers to be flexible and holistic. To date, the knowledge translation literature describes theory use and development as a linear and discrete process in line with more traditional scientific thinking and the search for understanding causation [21, 22]. Looking to other methodologies that are less concerned with causation and more focused on explanatory understanding and action (such as realist evaluation) [33] may limit reductionism, and provide enlightening findings about the interactions and complexities involved in knowledge translation activity [23]. However, we still need to be mindful of the relationship between the theory and the subsequent methodology and consider their fit with each other and with philosophical perspectives. 2ff7e9595c