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

D&I Pre-Conference Workshop

December 8th, 1pm ET | Intervention Optimization for Implementation Scientists CADIO will co-host a pre-conference workshop with GCIS introducing MOST and how it can be used to design and optimize multi-component implementation strategies, or bundles of multiple implementation strategies. Click here to register.

Dear Caddy…

How would you respond if, in a summary statement, one of the reviewers said that MOST can no longer be considered innovative? Sincerely, Asking for a Friend   Read the answer here.  

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.

Resources

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

Events

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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