Causal Inference in Studies with Functional Unmasking: Psychedelics and Beyond

Summary

Functional unmasking, or unblinding, is a significant issue in clinical trials for mental health treatments, particularly with psychedelics due to their clear acute effects. The findings highlight how traditional methods may obscure or exaggerate therapeutic benefits due to feedback between perceived benefits and expectancies. A new approach using modern causal inference techniques is proposed to better isolate true treatment effects and improve trial designs and statistical methods to address this challenge.

Study at a glance

Abstract

In clinical trials for mental health treatments, functional unmasking (unblinding) is a widespread challenge wherein participants become aware of their assigned treatment. Unmasking is especially concerning with psychedelics, due to the near unmistakable acute effects (the “trip”), resulting in uncertainty about whether outcomes following treatment reflect true therapeutic properties of the interventions, or placebo-like effects. We present a counterfactual conceptualization of unmasking that 1) formalizes the shortcomings of many existing statistical and experimental design solutions (e.g., dose-response, active controls), and 2) demonstrates how modern causal inference approaches can be applied to isolate effects devoid of this “contamination.” Our results reveal feedback mechanisms between perceived therapeutic benefits and expectancies that can render traditional methods prone to obscuring or exaggerating therapeutic benefits. Our proposal motivates trial designs and statistical methods that can be implemented to mitigate the impacts of functional unmasking.