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Mon, March 13, 2017, noon:
Rachel Best

Experimental Design and Primary Data Analysis Methods for Comparing Adaptive Interventions

Publication Abstract

Nahum-Shani, I., M. Qian, Daniel Almirall, W. Pelham, B. Gnagy, G. Fabiano, J. Waxmonsky, J. Yu, and Susan A. Murphy. 2012. "Experimental Design and Primary Data Analysis Methods for Comparing Adaptive Interventions." Psychological Methods, 17(4): 457-477.

In recent years, research in the area of intervention development has been shifting from the traditional fixed-intervention approach to adaptive interventions, which allow greater individualization and adaptation of intervention options (i.e., intervention type and/or dosage) over time. Adaptive interventions are operationalized via a sequence of decision rules that specify how intervention options should be adapted to an individual's characteristics and changing needs, with the general aim to optimize the long-term effectiveness of the intervention. Here, we review adaptive interventions, discussing the potential contribution of this concept to research in the behavioral and social sciences. We then propose the sequential multiple assignment randomized trial (SMART), an experimental design useful for addressing research questions that inform the construction of high-quality adaptive interventions. To clarify the SMART approach and its advantages, we compare SMART with other experimental approaches. We also provide methods for analyzing data from SMART to address primary research questions that inform the construction of a high-quality adaptive intervention.

DOI:10.1037/a0029372 (Full Text)

PMCID: PMC3825557. (Pub Med Central)

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