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.

MOST from a Conceptual Perspective

May Training: Now Accepting Applications

Our next virtual training on intervention optimization will be held from May 20-23, 2024. Applications are now open and will be accepted through March 22. Please visit the "Training" page under "cadio Academy" for more information.

Featured Event

Upcoming Webinar: March 27th

Dr. David Vanness, Professor at Penn State, will give a background on the history of using economic evaluation methods to evaluate interventions and present the case that the DAIVE approach may offer advantages over traditional cost-effective analysis (CEA) as a decision-making tool in the optimization phase of MOST. Head over to the Events page to sign up.

Intervention Optimization

Intervention optimization is a different way of thinking for intervention scientists. Here you’ll understand the rationale behind and the goal(s) of intervention optimization.

Cadio Academy

Increasing capacity of scientists working in the intervention optimization space across a variety of disciplines is central to cadio’s mission.


This is your one stop shop for tools and information to navigate through the intervention optimization process.


Watch this space for announcements for upcoming workshops, webinars, and other learning opportunities.

Further Learning

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.

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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