Applying the resource management principle to achieve community engagement and experimental rigor in the multiphase optimization strategy framework

Abstract

Preventing and treating mental health and substance use problems requires effective, affordable, scalable, and efficient interventions. The multiphase optimization strategy (MOST) framework guides researchers through a phased and systematic process of developing optimized interventions. However, new methods of systematically incorporating information about implementation constraints across MOST phases are needed. We propose that early and sustained integration of community-engaged methods within MOST is a promising strategy for enhancing an optimized intervention's potential for implementation. In this article, we outline the advantages of using community-engaged methods throughout the intervention optimization process, with a focus on the Preparation and Optimization Phases of MOST. We discuss the role of experimental designs in optimization research and highlight potential challenges in conducting rigorous experiments in community settings. We then demonstrate how relying on the resource management principle to select experimental designs across MOST phases is a promising strategy for maintaining both experimental rigor and community responsiveness. We end with an applied example illustrating a community-engaged approach to optimize an intervention to reduce the risk for mental health problems and substance use problems among children with incarcerated parents.