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Am J Prev Med. 2016 Oct;51(4 Suppl 2):S124-31. doi: 10.1016/j.amepre.2016.05.011. Epub 2016 Jun 28.

The Adaptome: Advancing the Science of Intervention Adaptation.

Author information

1
Division of Cancer Control and Population Sciences, National Cancer Institute, Bethesda, Maryland. Electronic address: dchamber@mail.nih.gov.
2
Division of Cancer Control and Population Sciences, National Cancer Institute, Bethesda, Maryland.

Abstract

In the past few decades, prevention scientists have developed and tested a range of interventions with demonstrated benefits on child and adolescent cognitive, affective, and behavioral health. These evidence-based interventions offer promise of population-level benefit if accompanied by findings of implementation science to facilitate adoption, widespread implementation, and sustainment. Though there have been notable examples of successful efforts to scale up interventions, more work is needed to optimize benefit. Although the traditional pathway from intervention development and testing to implementation has served the research community well-allowing for a systematic advance of evidence-based interventions that appear ready for implementation-progress has been limited by maintaining the hypothesis that evidence generation must be complete prior to implementation. This sets up the challenging dichotomy between fidelity and adaptation and limits the science of adaptation to findings from randomized trials of adapted interventions. The field can do better. This paper argues for the development of strategies to advance the science of adaptation in the context of implementation that would more comprehensively describe the needed fit between interventions and their settings, and embrace opportunities for ongoing learning about optimal intervention delivery over time. Efforts to build the resulting adaptome (pronounced "adapt-ohm") will include the construction of a common data platform to house systematically captured information about variations in delivery of evidence-based interventions across multiple populations and contexts, and provide feedback to intervention developers, as well as the implementation research and practice communities. Finally, the article identifies next steps to jumpstart adaptome data platform development.

PMID:
27371105
PMCID:
PMC5030159
DOI:
10.1016/j.amepre.2016.05.011
[Indexed for MEDLINE]
Free PMC Article

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