The Multiphase Optimization Strategy (MOST) and the Sequential Multiple Assignment Randomized Trial (SMART)

Abstract

In this article two new methods for building and evaluating eHealth interventions are described. The first is the Multiphase Optimization Strategy (MOST). It consists of a screening phase, in which intervention components are efficiently identified for inclusion in an intervention or for rejection, based on their performance; a refining phase, in which the selected components are fine tuned and issues such as optimal levels of each component are investigated; and a confirming phase, in which the optimized intervention, consisting of the selected components delivered at optimal levels, is evaluated in a standard randomized controlled trial. The second is the Sequential Multiple Assignment Randomized Trial (SMART), which is an innovative research design especially suited for building time-varying adaptive interventions. A SMART trial can be used to identify the best tailoring variables and decision rules for an adaptive intervention empirically. Both the MOST and SMART approaches use randomized experimentation to enable valid inferences. When properly implemented, these approaches will lead to the development of more potent eHealth interventions.

Introduction

There are good reasons to believe that interventions based on eHealth principles have the potential for considerable public health impact. Perhaps the most obvious reason is the reach of these interventions. Once an electronic intervention has been designed and programmed, delivery occurs via methods such as the Internet or by mailing a CD, and therefore it is extremely convenient. Moreover, the incremental cost of delivering an intervention to additional people usually is negligible, certainly in comparison to traditional interventions where, to deliver the program to more recipients, it becomes necessary to add additional physicians, therapists, health educators, peer counselors, and so on. The limiting factor for reach of an e-intervention is less likely to be a shortage of resources for delivering the program electronically than access to computers on the part of potential recipients. However, access to computers continues to increase in all strata of American society, suggesting that eHealth interventions hold growing promise.¹

The broad reach of eHealth interventions is particularly exciting in the light of some new methods for building and optimizing behavioral interventions. The purpose of this article is to introduce two of these new methods to eHealth scientists. One is the Multiphase Optimization Strategy (MOST)² for building and evaluating interventions in such a way that they are made out of active program components delivered at optimal doses. The other is the Sequential Multiple Assignment Randomized Trial (SMART)³ for building adaptive interventions. We propose that these new methods, although relatively untried at this writing, are eminently practical and hold much potential for eHealth research. By using these methods, it is possible to produce more potent interventions that, when coupled with the reach afforded by eHealth approaches, will promise considerable overall public health impact.