Moving beyond the treatment package approach to developing behavioral interventions: addressing questions that arose during an application of the Multiphase Optimization Strategy (MOST)

Abstract

Given current pressures to increase the public health contributions of behavioral interventions, intervention scientists may wish to consider moving beyond the classical treatment package approach that focuses primarily on achieving statistical significance. They may wish also to focus on goals directly related to optimizing public health impact. The Multiphase Optimization Strategy (MOST) is an innovative methodological framework that draws on engineering principles to achieve more potent behavioral interventions. MOST is increasingly being adopted by intervention scientists seeking a systematic framework to engineer an optimized intervention. As with any innovation, there are challenges that arise with early adoption. This article describes the solutions to several critical questions that we addressed during the firstever iterative application of MOST. Specifically, we describe how we have applied MOST to optimize an online program (myPlaybook) for the prevention of substance use among college student-athletes. Our application of MOST can serve as a blueprint for other intervention scientists who wish to design optimized behavioral interventions. We believe using MOST is feasible and has the potential to dramatically improve program effectiveness thereby advancing the public health impact of behavioral interventions. KEYWORDSMultiphase Optimization Strategy, Intervention d e v e l o p m e n t , S u b s t a n c e u s e p r e v e n t i o n , Experimental design Due to growing expectations that behavioral interventions should have a clinically meaningful public health impact, intervention scientists have started considering how to optimize their programs. A program has been optimized when it meets a priori criteria, expressed in terms of attributes such as efficacy, effectiveness, efficiency, or cost-effectiveness. One approach to achieving this goal is to use the Multiphase Optimization Strategy (MOST) developed by . MOST is a framework for program development and evaluation that is inspired by approaches used in engineering research and product development [1,4]. Using MOST allows intervention scientists to optimize behavioral interventions by specifying a desired criterion and systematically engineering the program to meet this criterion.MOST consists of three phases: Preparation, Optimization, and Evaluation. In the Preparation phase, intervention scientists draw on one or more theories to develop a conceptual model that will form the basis for the behavioral intervention. As part of this phase, they also identify which components, or parts of the intervention, to evaluate and develop and pilot those components. Finally, they select the desired optimization criterion, such as achieving a clinically meaningful public health impact (e.g., a specific effect size). In the Optimization phase, intervention scientists conduct one or more experiments to obtain information about the performance of each component. This information is used to decide which components should be retained to form the optimized inter...

Applying and advancing behavior change theories and techniques in the context of a digital health revolution: proposals for more effectively realizing untapped potential

“…Although this framework is still fairly new, MOST has been applied to a wide range of interventions targeting health behaviors, including smoking cessation (Collins et al, 2011; Strecher et al, 2008), weight loss (Pellegrini, Hoffman, Collins, & Spring, 2014), and drug use prevention among NCAA athletes (Wyrick, Rulison, Fearnow-Kenney, Milroy, & Collins, 2014), with a few applications using web- and app-based technologies (Pellegrini et al, 2014; Strecher et al, 2008; Wyrick et al, 2014). Although MOST can be used for traditional intervention delivery channels, as interventions move to digital platforms, the cost of data collection needed for running any study can be cut substantially, making these techniques accessible to far more researchers; that is, if they are familiar with this method and trained to use it.…”

An Overview of Research and Evaluation Designs for Dissemination and Implementation

“…We can consider testing a large number of components that go into an implementation strategy using Multiphase Optimization Strategy Implementation Trials (MOST) (29, 32, 69, 85, 91, 112). This approach recognizes that many choices can be made in an implementation strategy.…”

Improved Designs for Cluster Randomized Trials

“…However, it is relatively straightforward to analyze data from such studies using a multilevel modeling framework (60). A few examples of the use of fractional factorial designs for health behavior research can be found in Nair et al (42) and in Strecher et al (53).…”