Why conduct a factorial optimization trial?

Linda Collins, Ph.D.
Pennsylvania State University

ABSTRACT:
Behavioral interventions are used widely for prevention and treatment of health problems, and for promotion of well-being and academic achievement.  These interventions are typically developed and evaluated using the classical treatment package approach, in which the intervention is assembled a priori and evaluated by means of a two-group randomized controlled trial (RCT).   I will describe an alternative framework for developing, optimizing, and evaluating behavioral interventions.  This framework, called the multiphase optimization strategy (MOST), is a principled approach that has been inspired by ideas from engineering.  MOST includes the RCT for evaluation, but also includes other steps before the RCT, including one or more optimization trials.  Optimization trials are experiments that gather the empirical information needed to optimize an intervention.  Optimization trials can be conducted using any experimental design, but factorial designs are often the most efficient and economical.  Factorial designs have been around for more than one hundred years, and remain widely used in many fields, such as agriculture and engineering.  However, behavioral scientists are typically not trained in the potential advantages of factorial experiments, and how best to use them as a tool for intervention optimization.  In this webinar I will first introduce MOST.  I will then focus on factorial experiments, particularly on why they are an important alternative for conducting an optimization trial in MOST.