Evolution in Knowledge Translation Theories, Models, and Frameworks

The need for sound conceptual guidance has been an essential component guiding our quest for effective and sustainable evidence-based change in a variety of systems (i.e., individual, community, or organizational). Without guidance for critical reflection on KT’s key elements, it can be difficult to understand or explain why a particular endeavor may succeed or fail (Nilsen, 2015; Tabak, Khoong, Chambers, & Brownson, 2012).

There is no overarching KT approach that can meet all needs; rather, the KT approach must be tailored to a KT goal and context. While some theories, models, and frameworks (TMFs) pertain to dissemination, an overwhelming number are implementation-specific, addressing implementation process, determinant factors, strategies, and evaluation. The following section reflects on the evolution of TMFs within KT and implementation and draws attention to a select few examples.

Although TMFs tend to be viewed synonymously, they are unique in their assumptions and goals and, as a result, differ in their scope of inquiry. In some cases, there also may be overlap between TMFs, which can further generate confusion in understanding which TMFs are best suited for a KT undertaking. Some key distinctions among TMFs are presented in the following paragraphs, and Table 2 provides a brief overview.

A theory typically presents a set of principles, interrelated concepts, definitions, and/or propositions that aim to describe and explain events. Theories can be classified as descriptive, explanatory, or predictive, and can provide systematic guidance to help predict and examine which factors influence an outcome. Many theories are often described as “meta” theories that are broadly applicable, conceptual in nature, and not targeted to a particular context. Theories that have been applied to the field of KT include the Theory of Planned Behavior (Ajzen, 1985, 2005), the Theory of Diffusion (Rogers, 2003), and Social Cognitive Theory (Bandura, 1977, 1986, 2005).

A model seeks to describe—but not explain. Although models also can be quite conceptual, they aim to simplify understanding. The CIHR Model of KT and the Knowledge-to-Action (KTA) Model are examples. The CIHR Model of KT is “a global KT model, based on a research cycle, that could be used as a conceptual guide for the overall KT process” (Sudsawad, 2007, para. 21). The model identifies six opportunities for knowledge exchange in research, including defining research questions and methodologies; conducting research; publishing research findings in plain language and accessible formats; placing research findings into the context of other knowledge and socio-cultural norms; using research to inform decision-making decisions; and influencing subsequent research (CIHR, 2005). The KTA Model (Graham et al., 2006) is a first-generation process model that conceptualizes the relationship between knowledge creation and action. The KTA Model captures the need for evidence to be synthesized before its application and outlines the activities needed for implementation or application at a high, conceptual level. More recent TMFs, such as the Quality Implementation Framework (Myers, Durlak, & Wandesman, 2012), have gone further to describe the specifics of each process stage in greater detail.

Finally, a framework provides structured description of a given phenomenon via a series of concepts, categories, or variables, but does not necessarily explain the mechanism or ‘why’ a particular phenomenon unfolds the way it does. Common implementation frameworks include the Promoting Action on Research Implementation in Health (PARiHS) (Kitson et al., 2008) framework and updated iPARiHS (Harvey & Kitson, 2016), and the Consolidated Framework for Implementation Science (CFIR) (Damschroder et al., 2009).

Table 2. Distinctions Among Theories, Models, and Frameworks

	Brief Overview	Examples
Theory	Highly conceptual; non-context specific Aims to describe and explain a particular KT phenomenon through the presence of interrelated concepts, definitions, and/or propositions	Theory of Planned Behavior Theory of Diffusion Social Cognitive Theory
Model	Seeks to describe, but does not explain Presents a more defined scope of inquiry	CIHR Model of KT Knowledge-to-Action Model
Framework	Provides a systematic way to assess and evaluate the phenomenon under investigation Focus is more on what is occurring than on why it is occurring	PARiHS CFIR Quality Implementation Framework

Classifications and Taxonomies: Organizing the Deluge

KT has generated and incorporated theoretical and conceptual development in several fields. Theories within psychology, such as the Theory of Planned Behavior (Ajzen, 1985, 2005), the Theory of Reasoned Action (Fishbein & Ajzen (1975), and the Social Cognitive Theory (Bandura, 1977, 1986) have been widely applied to understand determinants associated with behavior change and user/adopter characteristics. Elsewhere, complexity science has emphasized that health care is a complex adaptive system: Linear implementation of evidence into practice is not feasible. “Complexity science forces us to consider the dynamic properties of systems and the varying characteristics that are deeply enmeshed in social practices, whilst indicating that multiple forces, variables, and influences must be factored into any change process, and that unpredictability and uncertainty are normal properties of multi-part, intricate systems” (Braithwaite, Churruca, Long, Ellis, & Herkes, 2018, p. 1).

Many TMFs elucidate greater understanding of diffusion, dissemination, adoption, and implementation. The term “KT,” however, is often conflated with IS, particularly in Canada, which obscures the possibility that KT may pertain to sharing knowledge and informing decision-making, in addition to facilitating practice, behavior, and policy change. KT and IS are related but not synonymous. As noted earlier, we view KT as an overarching term and implementation as a sub-specialty that relates to the goals of facilitating practice, behavior, and policy change based on evidence.

While the myriad of TMFs has broadened our understanding of key factors influencing the translation of evidence, they have also resulted in a deluge of diverse and, sometimes, similar approaches that can be complex and challenging to navigate, select, and apply. In recent years, researchers have sought to distill the complexity of TMFs and guide implementers through the creation of various classification systems. TMFs have been classified according to key characteristics or overarching aim. A few categorizations are highlighted below, including those aiming to guide implementers in selecting TMFs that best suit their KT goals.

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