Adaptive Intervention: Healing with Data - Maximizing Treatment Efficacy

Explore the potential of adaptive intervention in maximizing treatment efficacy for chronic diseases and addiction in this 1-hour 15-minute lecture by statistician Susan Murphy. Delve into the concept of implementing decision rules that dynamically adapt treatment to individual patient responses over time. Learn about avoiding over-treatment and providing increased care only to those who need it. Examine real-world examples, including adaptive drug court programs and studies on drug-addicted pregnant women. Understand the principles of SMART (Sequential Multiple Assignment Randomized Trial) designs and their application in various scenarios. Investigate Q-Learning techniques using data on children with ADHD and discover how to construct adaptive intervention proposals. Gain insights into delayed therapeutic effects, sample selection effects, and the importance of considering individual differences in patient response, risk, burden, adherence, and preference when developing treatment approaches.

Intro
Outline
Example of an Adaptive Intervention
Adaptive Drug Court Program
Jones' Study for Drug-Addicted Pregnant Women
An Adaptive Intervention in Blue
Delayed Therapeutic Effects
Sample Selection Effects
Examples of "SMART" designs
SMART Design Principles
SMART Designing Principles: Primary Hypothesis
Pelham ADHD Study
Q-Learning using data on children with ADHD
Constructing the Dependent Variable, Ý for the Stage 1 Regression
1st Adaptive Intervention Proposal
ADHD Example
2nd Adaptive Intervention Proposal