4.6 Article

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

期刊

AMERICAN JOURNAL OF PREVENTIVE MEDICINE
卷 32, 期 5, 页码 S112-S118

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ELSEVIER SCIENCE INC
DOI: 10.1016/j.amepre.2007.01.022

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资金

  1. NCI NIH HHS [P50 CA101451, P50 CA101451-04] Funding Source: Medline
  2. NIDA NIH HHS [K05 DA018206-03, K02 DA015674, P50 DA010075-10, K02 DA015674-05, K05 DA018206, P50 DA010075, P50 DA10075, K02 DA15674] Funding Source: Medline

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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.

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