Volume 10 Supplement 1
Disseminating evidence-based interventions to new populations: a systematic approach to consider the need for adaptation
© Hartman et al. 2015
Published: 14 August 2015
Audience segmentation or targeting interventions towards population subgroups, such as ethnic or racial groups, is hypothesized to increase the likelihood of intervention's relevancy and effectiveness on promoting health behaviors. Therefore, evidence-based interventions (EBIs) developed for a population other than the one of interest are often considered as non-relevant, hindering dissemination. Adaptation of EBIs to new populations of interest can solve this problem, but is discouraged since it can harm effective elements. There is little guidance on how to critically consider the need for adaptation. We present a framework that guides dissemination and implementation researchers and practitioners on how to make informed decisions on whether or not to adapt interventions or aspects of them.
We integrated models of ethnicity-based segmentation/ targeting of interventions, intervention planning, and formative evaluations of complex interventions into one framework to give guidance on how to systematically inform adaptation decisions. First, we suggest needs assessments to inform initial adaptation decisions. The framework distinguishes four intervention aspects to make individual adaptation decisions for (whether to retain aspects or to adapt them): behavioral goals, methods and strategies, intervention execution, and channels for delivery. We argue for assessing differences as well as similarities between target populations to make a subjective evaluation on whether those differences may affect EBIs' effectiveness in a way that they require adaptation. Subsequently, we recommend formative evaluations testing cultural relevancy to revise decisions if necessary, before large-scale implementation and evaluation are done among the new population.
Our framework can contribute to the dissemination of EBIs to other populations than the ones they were originally developed for. The framework discourages making more adaptations than necessary by critically and systematically assessing the need for adaptation. As a consequence, it increases the likelihood of retaining effective elements.
This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.