Center for Advancement and Dissemination of Intervention Optimization (cadio)
Intervention optimization is an emerging scientific field. In this field ideas from behavioral science, engineering, public health, quantitative and qualitative methods, economics, and decision science are integrated to produce innovative approaches for empirical development and optimization of interventions.
Whether you are looking for additional support as you prepare a grant proposal involving MOST or practical information helpful in managing your optimization trial, this section provides resources for a deeper dive into intervention optimization.
REDCap with Most
The goal of this manual is to show how one might setup a REDCap project to support a research study with multiple conditions, such as factorial experiments common in the Multiphase Optimization Strategy (MOST) framework.
Establishing a conceptual model and understanding optimization
Sometimes the conceptual model is not a model of a health behavior per se, but a model of maintaining treatment fidelity, promoting adherence or compliance, or the like. The conceptual model is explained in more...
Common misconceptions about factorial experiments
A factorial experiment is essentially an RCT with a lot of experimental conditions, and therefore is extremely difficult to power.
Informal introduction to factorial experimental designs
The purpose of this page is to clarify some concepts, notation, and terminology related to factorial experimental designs, and to compare and contrast factorial experiments to randomized controlled trials (RCTs). A more in-depth introduction can...
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