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Updated: Nov 9, 2025

A Novel Method for Involving Women of Color at High Risk for Preterm Birth in Research Priority Setting
Published on: January 12, 2018
Enhancing behavioral intervention science: using community-based participatory research principles with the
Liliane Cambraia Windsor1, Ellen Benoit2, Rogério M Pinto3
1School of Social Work, The University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA.
Abstract:
Innovative methodological frameworks are needed in intervention science to increase efficiency, potency, and community adoption of behavioral health interventions, as it currently takes 17 years and millions of dollars to test and disseminate interventions. The multiphase optimization strategy (MOST) for developing behavioral interventions was designed to optimize efficiency, efficacy, and sustainability, while community-based participatory research (CBPR) engages community members in all research steps. Classical approaches for developing behavioral interventions include testing against control interventions in randomized controlled trials. MOST adds an optimization phase to assess performance of individual intervention components and their interactions on outcomes. This information is used to engineer interventions that meet specific optimization criteria focused on effectiveness, cost, or time. Combining CBPR and MOST facilitates development of behavioral interventions that effectively address complex health challenges, are acceptable to communities, and sustainable by maximizing resources, building community capacity and acceptance. Herein, we present a case study to illustrate the value of combining MOST and CBPR to optimize a multilevel intervention for reducing substance misuse among formerly incarcerated men, for under $250 per person. This integration merged experiential and cutting-edge scientific knowledge and methods, built community capacity, and promoted the development of efficient interventions. Integrating CBPR and MOST principles yielded a framework of intervention development/testing that is more efficient, faster, cheaper, and rigorous than traditional stage models. Combining MOST and CBPR addressed significant intervention science gaps and speeds up testing and implementation of interventions.
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