Optimization of implementation strategies using the Multiphase Optimization STratgey (MOST) framework: Practical guidance using the factorial design.

Transl Behav Med

Department of Social and Behavioral Sciences, School of Global Public Health, New York University, New York, NY, USA.

Published: September 2024

AI Article Synopsis

  • - The Multiphase Optimization STrategy (MOST) framework consists of three phases—preparation, optimization, and evaluation—to create effective interventions while ensuring they are affordable, scalable, and efficient.
  • - MOST focuses on optimizing both the intervention components and the implementation strategies, which are key to delivering the intervention successfully.
  • - The article discusses four scenarios where MOST can be applied to improve implementation strategies, using school-based physical activity examples to clarify the concepts and offering data to help researchers make informed decisions in their own trials.

Article Abstract

The Multiphase Optimization STrategy (MOST) is a framework that uses three phases-preparation, optimization, and evaluation-to develop multicomponent interventions that achieve intervention EASE by strategically balancing Effectiveness, Affordability, Scalability, and Efficiency. In implementation science, optimization of the intervention requires focus on the implementation strategies-things that we do to deliver the intervention-and implementation outcomes. MOST has been primarily used to optimize the components of the intervention related to behavioral or health outcomes. However, innovative opportunities to optimize discrete (i.e. single strategy) and multifaceted (i.e. multiple strategies) implementation strategies exist and can be done independently, or in conjunction with, intervention optimization. This article details four scenarios where the MOST framework and the factorial design can be used in the optimization of implementation strategies: (i) the development of new multifaceted implementation strategies; (ii) evaluating interactions between program components and a discrete or multifaceted implementation strategies; (iii) evaluating the independent effects of several discrete strategies that have been previously evaluated as a multifaceted implementation strategy; and (iv) modification of a discrete or multifaceted implementation strategy for the local context. We supply hypothetical school-based physical activity examples to illustrate these four scenarios, and we provide hypothetical data that can help readers make informed decisions derived from their trial data. This manuscript offers a blueprint for implementation scientists such that not only is the field using MOST to optimize the effectiveness of an intervention on a behavioral or health outcome, but also that the implementation of that intervention is optimized.

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Source
http://dx.doi.org/10.1093/tbm/ibae035DOI Listing

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