I’ve conducted an optimization trial and analyzed the data. Now my team is going to use the results to optimize our intervention! I am excited but nervous. Do you have any advice?
This IS exciting! Congratulations on having arrived at this point. It took a lot of hard work to get there!
First, we recommend making sure to allow enough time for the decision-making process. A bare minimum of two hours will be needed, very likely more.
Second, have plots of any interactions handy.
Third, before you conduct the decision-making “for real” on your own data, consider conducting a realistic practice exercise with your team using one of the data sets and accompanying documentation we provide for this purpose. These are artificial data, so no need to be concerned about obtaining IRB approval. This exercise may be a useful warm-up before the real thing.
All Frequently Asked Questions
Do you see MOST intersecting with implementation science, and if so, how?
Can I expect reviewers of grant proposals to understand MOST? If not, how should I handle this in the application? There is not enough room to provide a lot of background.
I work in the prevention field, in which the horizon on the outcome is very far away. How can I optimize under these circumstances? It seems like it would take decades.
Should I apply for funding to support all three phases of MOST?
How can I find out what other studies using MOST have been conducted in my area?
How can I obtain the background I need to write a grant proposal involving MOST?
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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