The Multiphase Optimization Strategy (MOST) and the Sequential Multiple Assignment Randomized Trial (SMART) - New methods for more potent eHealth interventions

被引:700
作者
Collins, Linda M.
Murphy, Susan A.
Strecher, Victor
机构
[1] Penn State Univ, Methodol Ctr, State Coll, University Pk, PA 16801 USA
[2] Penn State Univ, Dept Human Dev & Family Studies, University Pk, PA 16802 USA
[3] Univ Michigan, Inst Social Res, Ann Arbor, MI 48109 USA
[4] Univ Michigan, Dept Stat, Ann Arbor, MI 48109 USA
[5] Univ Michigan, Dept Hlth Behav & Hlth Educ, Ann Arbor, MI 48109 USA
关键词
D O I
10.1016/j.amepre.2007.01.022
中图分类号
R1 [预防医学、卫生学];
学科分类号
1004 ; 120402 ;
摘要
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 (SNLART), 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.
引用
收藏
页码:S112 / S118
页数:7
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