Translation Science Theories and Models

Translation Science Theories and Models

Translation science is a concept that means testing implementation interventions to improve the uptake and application of available evidence for improving patient outcomes and population health. Translation science clarifies the implementation strategies that work for a particular population’s health in a specific setting and why.

Translation science models and theories provide frameworks to assess the impact of research applying scientific findings to promote public health and wellness (Titler, 2018). This discussion presents one translational science model in relation to the previously selected practice problem, components of the model, and common barriers to evidence translation in addressing the practice problem.

The selected practice problem is diabetes. Diabetes is a group of endocrine disorders characterized by challenges in blood sugar regulation in the body. There are three types of diabetes; type 1 diabetes, type 2 diabetes, and gestational diabetes. Diabetes is a condition that significantly impacts the healthcare system, the individual, the family, and society at large. It is the most expensive condition to treat and manage and negatively impacts the patient’s quality of life, thus a significant practice problem. One translational research model that can be used in addressing the practice problem is the RE-AIM framework.

RE-AIM is a translation science model initially developed to enhance the planning, evaluation, and implementation of public health evidence-based programs and interventions (Titler, 2018). It emphasizes five significant dimensions: reach, effectiveness, adoption, implementation, and maintenance. According to Esmail et al. (2020), RE-AIM is currently applied in planning the implementation stages of diverse areas of healthcare, such as disease management, prevention, and health promotion in various settings.

It is also used to report the results of evidence-based practice implementation. Diabetes affects the entire society, with its effects felt across all health populations. It mandates the healthcare system to carry out proper diabetes management, prevention, and health promotion using diabetes best practices and the available evidence-based practice. Therefore, the RE-AIM model can perfectly address the practice problem.

Various barriers to evidence translation can be encountered while addressing the practice problem. One of the significant barriers in evidence translation to addressing the diabetes practice problem is having a slow, haphazard and unpredictable translation process. Research shows that despite the high investment in health research to improve care delivery, the evidence translation remains slow and unpredictable, compromising the implementation of research findings into practice and health policy.

Similarly, there is extensive research on the various aspects and factors surrounding diabetes, its management, treatment, and prevention. However, health outcomes and public health concerning diabetes still lag behind due to the slow evidence translation process.

Another major barrier is the amount of time required for the verification to enhance the implementation of research findings into practice. Healthcare stakeholders must verify the findings and proposals from translational evidence before implementing them. For instance, various research on diabetes has been done focusing on specific populations. The findings from these studies must be verified, especially when the implementation is done on other health populations with similar characteristics, which takes time.

In conclusion, translation science theories and models are essential in providing a framework for implementing research and evidence in practice. The RE-AIM translation science model is one of the frameworks that can be used for diabetes. However, barriers such as time and slow translation processes exist. These barriers should be addressed to enhance better health outcomes and population well-being for diabetes patients, thus addressing the problem.


Edwards, A., Zweigenthal, V., & Olivier, J. (2019). Evidence map of knowledge translation strategies, outcomes, facilitators, and barriers in African health systems. Health research Policy And Systems17(1), 1-14.

Esmail, R., Hanson, H. M., Holroyd-Leduc, J., Brown, S., Strifler, L., Straus, S. E., Niven, D. & Clement, F. M. (2020). A scoping review of full-spectrum knowledge translation theories, models, and frameworks. Implementation Science15(1), 1-14.

Titler, M.G., (2018) “Translation Research in Practice: An Introduction” OJIN: The Online Journal of Issues in Nursing Vol. 23, No. 2, Manuscript 1.