Randomized treatment-belief trials.

Area of Science:

• Clinical Trials Methodology
• Causal Inference
• Health Services Research

Background:

• Traditional randomized controlled trials (RCTs) exhibit limited generalizability due to artificial trial conditions.
• Pragmatic trials aim to enhance real-world applicability by mimicking everyday clinical scenarios.
• Patient uncertainty regarding treatment assignment in RCTs differs from real-world prescription scenarios and can influence outcomes.

Purpose of the Study:

• To define causal effects considering both treatment assignment and patient beliefs about assignment.
• To highlight limitations of traditional RCTs in estimating relevant causal quantities.
• To propose a novel study design for more comprehensive causal effect estimation.

Main Methods:

• Utilized a potential outcomes framework to define causal effects.
• Incorporated combinations of treatment assignment and belief about treatment assignment into the causal model.
• Proposed a new study design to capture a broader spectrum of causal effects.

Main Results:

• Demonstrated that traditional RCTs estimate a causal effect that is often not the primary interest.
• Identified that patient uncertainty about treatment assignment can impact both treatment and placebo responses.
• Established the theoretical basis for a new study design.

Conclusions:

• Traditional RCTs may not adequately address the causal questions most relevant to clinical practice.
• A new study design is proposed to provide insights into a wider range of causal effects, enhancing clinical decision-making.
• Considering patient beliefs alongside treatment assignment offers a more nuanced understanding of treatment efficacy in real-world settings.