The difference between 'placebo group' and 'placebo control': a case study in psychedelic microdosing.
Balázs Szigeti, David Nutt, Robin Carhart-Harris, David Erritzøe
Sci Rep July 26, 2023 DOI: 10.1038/s41598-023-34938-7 via PubMed
Summary
AI-generated from the abstractBlinding in medical trials aims to evenly distribute expectancy effects between treatment groups, but it often fails. Using computational modeling, this work shows that weak blinding combined with positive treatment expectancy creates an 'activated expectancy bias' (AEB), which can inflate treatment effect estimates and produce false positive results. The authors introduce the Correct Guess Rate Curve (CGRC) to estimate outcomes of a perfectly blinded trial from imperfectly blinded data. Re-analyzing a self-blinding psychedelic microdose trial dataset, they find that observed placebo-microdose differences are susceptible to AEB and may be false positives, suggesting microdosing acts as an active placebo. The findings highlight the distinction between trials with a placebo control group and genuinely placebo-controlled trials.
Study at a glance
| Characteristics | Computational modeling with re-analysis of empirical data Placebo-controlled Case report Peer reviewed |
|---|---|
| Keywords | Placebo effect Expectation bias Mind-body connection Psychological impact Suggestion |
| Citations | 33 |
| Key finding | Weak blinding and positive treatment expectancy can produce activated expectancy bias, inflating treatment effects and risking false positive findings; microdosing may be understood as an active placebo. |
Abstract
In medical trials, 'blinding' ensures the equal distribution of expectancy effects between treatment arms in theory; however, blinding often fails in practice. We use computational modelling to show how weak blinding, combined with positive treatment expectancy, can lead to an uneven distribution of expectancy effects. We call this 'activated expectancy bias' (AEB) and show that AEB can inflate estimates of treatment effects and create false positive findings. To counteract AEB, we introduce the Correct Guess Rate Curve (CGRC), a statistical tool that can estimate the outcome of a perfectly blinded trial based on data from an imperfectly blinded trial. To demonstrate the impact of AEB and the utility of the CGRC on empirical data, we re-analyzed the 'self-blinding psychedelic microdose trial' dataset. Results suggest that observed placebo-microdose differences are susceptible to AEB and are at risk of being false positive findings, hence, we argue that microdosing can be understood as active placebo. These results highlight the important difference between 'trials with a placebo-control group', i.e., when a placebo control group is formally present, and 'placebo-controlled trials', where patients are genuinely blind. We also present a new blinding integrity assessment tool that is compatible with CGRC and recommend its adoption.