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All are examples of translational researchers converting molecular knowledge about specific cancer cells into effective, targeted therapies. The efficient movement of basic science discoveries into clinical applications—often described as "bench to bedside" work—is the goal of translational research.

Disis thinks the field is so promising she hopes her kids grow up to work in it. Future translational researchers of all ages must be adaptable, life-long learners, says Disis. This means being outside your comfort zone, reading literature that is way outside your field. A translational scientist should be able to move an idea all the way from basic research to a clinical application and back to the lab to inform more basic science. Handing off projects from one expert to another doesn't work, says Disis.

Success requires someone who understands the idea intimately, and who can build a multidisciplinary team to guide it along the translational path. It's a long journey with physical hurdles, since basic and clinical research labs usually reside in separate departments. There are also intellectual and cultural barriers. Basic science starts with a hypothesis and designs experiments that validate or reject it, with the goal of acquiring knowledge. Translational science starts with a health need and looks for scientific insights or tools to address that need.

The successful translational researcher needs to be comfortable in both of these cultures, be fluent in many fields, and thrive on collaboration. For those with medical training, this might mean learning about hypothesis-driven science and designing experiments and assays. For those with a research background, it could mean learning clinical study design and the bioethics of human research. In her translational science training program, she says, "I have a bioengineer who can now design a clinical trial. I love that he can do that, and he says it gives him a deeper understanding of his own research.

Training options include a Ph. For those who already have an M. Classes explain the basics of study design and methods, biostatistics, and bioethics. Because developing a new drug, device, or procedure is a team project, coursework might include team dynamics and management. However, for most trainees, the most valuable aspects of a training program are mentoring and hands-on experience in multidisciplinary research. This set of guidelines encourages cross-disciplinary, team-based research as a way to overcome obstacles to turning scientific discoveries into health solutions.

Currently, CTSAs have been granted to 55 institutions, with a plan to fund 60 institutions by The programs introduce elements of clinical training into basic science graduate work. They vary by institute, but range from Ph. These are guided by senior faculty, who also give advice on "their career trajectory, resources, funding mechanisms, partnerships that were successful—essentially life experience, and teaching us how to succeed in research.

For a bench scientist, a background in translational research turns the medical objective that is often written into a grant application into a real and achievable goal. This gives him both a postdoctoral research opportunity and guidance towards his long-term goal: "That my research has a high impact on public health. In turn, says Lanza, trainees benefit from having established clinical researchers as mentors and from working with experienced investigators from several disciplines.

Lanza's project illustrates another aspect of translational research: It's not always about designing the next cancer drug. It can be traditional bench work with an eye toward how the results might be applied to everyday health care. Lanza is not currently planning any clinical trials for his work on muscle mitochondrial physiology and function, but looking ahead, says, "I hope to provide some concrete recommendations for cost-effective, straightforward lifestyle choices that can preserve quality-of-life as people get older, not necessarily increasing their lifespan, but their health span.

To get a sense of the variety and diversity of translational research and the educational options, look through the online offerings hosted by each CTSA-funded site. The models build on the success of evidence based medicine. Key components of EBPH models include making decisions based on the best available peer-reviewed evidence; using data and information systems systematically; applying program-planning frameworks; and engaging the community. EBPH has emerged as a powerful framework for assessing public health concerns and identifying the most effective health protection strategies.

Number of studies: 6 citations 1 , Major changes over time: Nutbeam and Bauman 58 first developed the model; minor adaptations were made by Rychetnik et al. Context applied: Falls prevention, public health, child obesity prevention, chronic disease prevention.

ITHS | T-Phases of Translational Health Research

Key implications: The rocket model shows the different research and evaluation questions and research methods that are applied in the planning, evaluation and dissemination of a comprehensive set of public health interventions over six stages, and can be used to inform development of public policies and programs. The framework enables decision makers to map the evidence for a given policy or program — that is, to identify what types of evaluations have been done, including translation research, and what of this evidence if any informed current policy and practice.

The rocket model also provides a useful approach for assessing evidence gaps in health promotion programs, and highlights opportunities to improve the evidence base. Key implications: The ISF provides a heuristic for understanding the needs, barriers and resources of the different systems, as well as a structure for summarising existing research and illuminating priority areas for new research and action.

The model recognises the need to synthesise evidence and package the information to better meet the needs of target audiences. The ISF also recognises that the top-down approach to implementation is suboptimal, as implementation efforts require partnerships. Number of studies: 2 citations 43 , Key implications: The MRC framework guided the development of interventions that helped improve outcomes in patients with coronary heart disease and depression.

It also helped map the process for translating osteoporosis evidence into practice, and facilitated the selection of appropriate study designs to rigorously address barriers, evaluate outcomes and address sustainability. Frameworks included in the review have been applied in myriad settings, including basic and medical sciences, public health, clinical research, disease management, guideline development, global health, environmental health and preventive medicine. These frameworks can successfully support knowledge translation in a number of sectors across health and beyond.

The review identified 41 frameworks and models. The RE-AIM Reach, Efficacy, Adoption, Implementation and Maintenance framework has gained great prominence in the field of chronic disease management, and increasingly in public health. This framework assists in the planning, evaluation and reporting of applied research and interventions. Glasgow and colleagues 13 argue that reporting and documenting RE-AIM for efficacy trials and effectiveness interventions will help address slow adoption of research into practice because, by its nature, the framework provides information on generalisability and external validity of interventions.

There is merit in this argument, as the RE-AIM framework has been successfully applied in numerous real-world case studies. Examples include assessing the translatability of an effective community-based exercise intervention to prevent falls 21 ; examination of factors influencing the impact of a financial incentive—based smoking cessation intervention in a workplace 23 ; translation of a computer-assisted diabetes self-management intervention 27 ; implementation of a lifestyle intervention tool in primary care 17 ; and application to assessing the public health impact of policy change.

The framework has also been used to assess the generalisability of published health promotion literature 16 and to help design and plan public health interventions to improve dissemination. It also includes two translational steps T1 and T2 and describes how new medical discoveries are translated into clinical practice T2. Westfall et al. Though this model substantially advances the conceptual development of translation science, it does not acknowledge other important types of research, including community-based participatory research, public health research and health policy analysis.

An example of T4 from Khoury and colleagues 6 in genomics is that, although public health newborn screening programs have been in place for decades, they have only recently integrated new technologies particularly tandem mass spectrometry for identifying an expanded number of disorders.

THE CONTRIBUTION OF EPIDEMIOLOGY TO SCIENTIFIC DISCOVERIES

Surveillance and outcomes research are being used to document the real-world effectiveness and potential harms of these new tests. The types of research that characterise each phase include observational and clinical trials in T1; evidence synthesis and guideline development in T2; implementation research and dissemination research in T3; and outcomes research across disciplines and population monitoring in T4.

More recently, this model has incorporated an additional precursor stage, T0, in which the problem is identified. The model highlights that the true endpoint of translational research is not simply institutionalising effective interventions, but improving population health. Figure 2 shows the relationships across these phases in a further adaption of the model of Khoury and colleagues 6 by Glasgow and colleagues in Figure 2. T0—T4 phases of translational research click to enlarge. Knowledge creation includes knowledge inquiry, knowledge synthesis and the creation of knowledge tools.

The phases can occur sequentially or simultaneously, and the knowledge phases can influence the action phases at any point in the cycle. The elements of the action cycle focus on deliberately bringing about change in healthcare systems and groups.

Figure 3. Knowledge to Action KTA framework click to enlarge. The framework proposes that, for implementation to be successful, there needs to be clarity about the nature of the evidence used, the quality of the context, and the type of facilitation needed to ensure a successful change process. Figure 4. All these frameworks describe a gap between research knowledge and its application to treatment options, policy and practice, and acknowledge the importance of closing this gap.

They all articulate processes for applying evidence from research to intervention development, then applying interventions with demonstrated efficacy in controlled environments into new settings with different populations, and ultimately disseminating effective interventions into policy and practice. It is therefore not surprising that these models appear to lend themselves more readily to practical application in these respective fields.

This lack of consistent terminology can be a source of confusion. The concept of research translation in particular is increasingly recognised internationally as an important function of academia and is a growing priority for major health-related funders. All these frameworks acknowledge the difficulty of closing the gap between research and practice, and that this gap is in part caused by a failure of research to meet the information needs of policy makers and practitioners; characteristics of the intervention particularly if it is overly intensive, expensive and difficult to implement in other populations and settings ; and the research or evaluation designs giving insufficient attention to real-world contexts and the complex interaction of these factors.

The evidence based public health framework proposed by Brownson and colleagues 10 offers a practical evidence-to-practice approach and, in more recent iterations, acknowledges the importance of contextual implementation factors. Despite this, they are the most widely applied models by health funding bodies, particularly in the US and Australia. This drives public health and clinical researchers to use these narratives in describing translation efforts, even though they sit more naturally with basic and clinical sciences. It could be reasonably argued that this places public health researchers at a disadvantage, particularly because many of their translation outcomes are more distal than those of clinical researchers.

Encouragingly, there seems to be increasing recognition that the endpoint of translation is broader than clinical practice, and that it includes population health and system change. Interestingly, the only other models to have similar stages are the maintenance phase in RE-AIM 12 and the sixth program monitoring phase in the Nutbeam and Bauman model. Although RE-AIM provides a comprehensive and well-tested translation framework, there are a number of challenges to its practical application.

From the lab to the clinic and back: Translational research training and careers

The first is the expression of efficacy as positive outcomes minus negative outcomes. This oversimplifies the process of assessing the efficacy of an intervention, and is problematic because it is very difficult to quantify positive outcomes in a way that can be directly compared with negative outcomes. In addition, it does not give sufficient consideration to monitoring and reporting contextual factors that support or hinder the adoption and dissemination of promising interventions into broader policy and practice. The PARiHS framework came to prominence because of its explicit consideration of contextual factors as a critical aspect of successful implementation of programs and policies.

By treating evidence, context and facilitation as equally important in research translation, the framework supports researchers and policy makers to understand the full range of factors affecting translation of evidence into practice.

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The KTA framework is one of the few models not to have undergone significant revision since being developed in This is because Graham and colleagues 8 recognised that research translation is a continuous, cyclic process that requires continuous refinement over time. The framework acknowledges that research translation may not necessarily follow a pipeline model, and that each element in the translation process influences other elements. It also recognises that knowledge is constantly evolving and can feed into policy making at various stages.

2010 Translational Medicine Conference, 1 of 5

Finally, the model acknowledges that research evidence has to be adapted to the local context to be useful in informing policy and practice. As a result, the model has been highly successful and adopted as a national research translation framework in Canada. All these models would benefit from more detailed consideration of the processes associated with scaling up promising interventions within complex community and organisational contexts. Notably, none of the reviewed models specifically addresses costs. Cost, cost effectiveness and cost benefit are often key factors in determining how widely adopted an intervention will be in practice, and could figure more prominently in these models.

Despite its potential usefulness as a conceptual model, the Nutbeam and Bauman model is yet to be widely tested using real-world case studies in policy and practice. This may be partly explained by the fact that the model is a relatively new arrival, first published in In contrast, the most commonly applied model in the literature, RE-AIM, was first published in the peer-reviewed literature in , allowing more time for the model and associated concepts to permeate thinking in the field.

It is important to consider the comparative effectiveness of these frameworks in supporting the development and implementation of successful programs and policies. All the frameworks in this review have the common goal of bridging the gap between evidence and practice. Understanding which is most effective and in what contexts will support the development of better policies and programs that have the greatest impact on improving population health.

Further, more work is needed to determine how research translation frameworks are being used by researchers, policy makers and institutions. This review has identified a number of published case studies, all of which demonstrated successful application of research translation frameworks. We encourage authors to document accounts of successful and unsuccessful application of these frameworks in real-world case studies and, importantly, encourage journals to publish these data. To comprehensively investigate the relative success of the application of these frameworks, further research involving document analysis and interviews with users of these frameworks is recommended.

A better understanding of how research translation frameworks are being used in health policy and program development will allow us to better identify the key challenges to effective research translation and assist in understanding the role that these frameworks can potentially play in bridging the evidence—practice gap. A single database was searched for this review, which may mean that papers were missed. However, PubMed is a large database, so it is likely that the most relevant frameworks and models were identified.

The study applied a systematic review methodology with narrative synthesis, which differs from approaches used in Cochrane reviews. This decision was made as the topic under consideration was better suited to narrative analysis. Conceptual models for research translation are interpreted and applied by different health fields in different but related ways. All of the reviewed models acknowledge a gap between research knowledge and its application to treatment options, policy and practice, and propose pathways to closing this gap. All the models articulate processes of applying evidence from research to intervention development, then applying interventions with demonstrated efficacy into new settings with different populations, and ultimately disseminating effective interventions into policy and practice.

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Introduction

Advanced search. Toggle navigation. Home Issues February , Volume 27, Issue 1 Narrative review of frameworks for translating research evidence into policy and practice. Collapse all. Expand all. Author details. Corresponding author Andrew J Milat amila doh. Competing interests None declared. Author contributions AM developed the concept for the paper, framed the search strategy, categorised papers and led the manuscript production. Full text. Introduction Methods Results Discussion Conclusion.


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Methods Literature review search strategy The review included publications on theoretical frameworks and models that describe processes and issues associated with translation of research evidence into policy and practice. Box 1. Most frequently applied research translation frameworks and models RE-AIM Number of studies: 17 citations Key elements: Reach proportion of the target population that participated in the intervention Efficacy or effectiveness success rate if implemented, e.

Context applied: Postoperative pain management, nursing, neonatal health. Evidence based public health EBPH models Number of studies: 6 citations 10 , Key elements: Community assessment Quantifying the issue Developing a concise statement of the issue Determining what is known through the scientific literature Developing and prioritising a policy or program Developing plans and implementing interventions Evaluating the policy or program.

Stages of research progression rocket model Number of studies: 6 citations 1 , Key elements: Problem definition Solution generation program development Intervention testing process and impact evaluation to determine program efficacy or effectiveness Intervention replication effective programs are adapted for other settings to determine if similar outcomes can be reproduced Dissemination research upscaling of a program to a population-wide level. Interactive Systems Framework for Dissemination and Implementation ISF Number of studies: 4 citations Key elements: Three levels: Implementing prevention — prevention delivery system general capacity use, innovation-specific capacity use Supporting the work — prevention support system general capacity building, innovation-specific capacity building Distilling the information — prevention synthesis and translation system.

These three levels are encapsulated by four pillars: Funding Macro policy Existing research and theory Climate. Major changes over time: None. Context applied: Teenage pregnancy. UK Medical Research Council MRC framework Number of studies: 2 citations 43 , 67 Key elements: A cycle consisting of: Development identifying the evidence base Feasibility and piloting testing procedures Evaluation assessing effectiveness Implementation dissemination, surveillance, follow-up. Context applied: Coronary heart disease and depression, osteoporosis. Table 1. RE-AIM evaluation dimensions Dimension a Level Reach proportion of target population that participated in the intervention Individual Efficacy success rate if implemented as in guidelines; defined as positive outcomes minus negative outcomes Individual Adoption proportion of settings, practices and plans that will adopt this intervention Organisation Implementation extent to which intervention is implemented as intended in the real world Organisation Maintenance extent to which program is sustained over time Individual and organisation a The product of the five dimensions is the public health impact score population-based effect.

T0—T4 phases of translational research click to enlarge Source: Glasgow et al. Strengths and weaknesses of the models when applied in practice The evidence based public health framework proposed by Brownson and colleagues 10 offers a practical evidence-to-practice approach and, in more recent iterations, acknowledges the importance of contextual implementation factors. Areas for further research It is important to consider the comparative effectiveness of these frameworks in supporting the development and implementation of successful programs and policies.

Limitations of the review A single database was searched for this review, which may mean that papers were missed. Conclusion Conceptual models for research translation are interpreted and applied by different health fields in different but related ways. Acknowledgements The authors thank Dr Michael Giffin for editing the manuscript. Translating research for evidence-based public health: key concepts and future directions. CrossRef PubMed 2.