The full translational spectrum of prevention science: facilitating the transfer of knowledge to practices and policies that prevent behavioral health problems

Transl Behav Med. 2016 Mar;6(1):5-16. doi: 10.1007/s13142-015-0376-2.

Abstract

A broad-span, six-stage translational prevention model is presented, extending from the basic sciences-taking a multi-level systems approach, including the neurobiological sciences-through to globalization. The application of a very wide perspective of translation research from basic scientific discovery to international policy change promises to elicit sustainable, population-level reductions in behavioral health disorders. To illustrate the conceptualization and actualization of a program of translational prevention research, we walk through each stage of research to practice and policy using an exemplar, callous-unemotional (CU) traits. Basic science has identified neurobiological, psychophysiological, behavioral, contextual, and experiential differences in this subgroup, and yet, these findings have not been applied to the development of more targeted intervention. As a result, there are currently no programs considered especially effective for CU traits, likely because they do not specifically target underlying mechanisms. To prevent/reduce the prevalence of conduct disorder, it is critical that we transfer existing knowledge to subsequent translational stages, including intervention development, implementation, and scaling. And eventually, once resulting programs have been rigorously evaluated, replicated, and adapted across cultural, ethnic, and gender groups, there is potential to institutionalize them as well as call attention to the special needs of this population. In this paper, we begin to consider what resources and changes in research perspectives are needed to move along this translational spectrum.

Publication types

  • Editorial
  • Review

MeSH terms

  • Animals
  • Conduct Disorder / prevention & control*
  • Humans
  • Translational Research, Biomedical / methods*