A RIGOROUS DOUBLE-BLIND RANDOMIZED-CONTROLLED TRIAL ON MICRODOSING PSILOCYBIN OVER EIGHT WEEKS
Bibliographic record
Abstract
While microdosing psilocybin—the practice of taking very small, non-hallucinogenic doses— has become more popular recently, especially for mood enhancement, there is a paucity of rigorous clinical research on its effects. This dissertation explores the therapeutic potential of microdosing psilocybin for treating symptoms of depression and anxiety and improving quality of life, addressing critical gaps in the literature surrounding its efficacy and mechanism of action. We conducted a phase II randomized controlled trial (RCT) involving 20 participants diagnosed with mild-to-moderate Major Depressive Disorder. Participants were assigned to either a psilocybin-first microdosing regimen (2 mg weekly) or placebo-first for four weeks, followed by an open-label crossover phase with 2mg of psilocybin for four additional weeks. The study assessed changes in multiple cognitive, state, and trait depressive symptoms, as well as anxiety and quality of life, using a comprehensive battery gold-standard measures. Findings revealed that while the microdosing regimen assessed here did not significantly reduce depressive symptoms, it had a significant positive impact on symptoms of anxiety and quality of life. Furthermore, we found that while participants were significantly better than chance at detecting whether they were in the psilocybin condition, they were still technically and legally unimpaired. Taken together, this research suggests that microdosing may be an effective treatment to symptoms of anxiety, and that the most accurate definition for microdosing is not a “sub-perceptual”, but rather an "unimpairing" dose. These promising results should be followed by additional data collection in larger trials to confirm or falsify our findings.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".