Microdosing psychedelics: Demographics, practices, and psychiatric comorbidities
Bibliographic record
Abstract
Rationale: Microdosing psychedelics – the practice of consuming small, sub-hallucinogenic doses of substances such as LSD or psilocybin – is gaining attention in popular media but remains poorly characterized. Contemporary studies of psychedelic microdosing have yet to report the basic psychiatric descriptors of psychedelic microdosers. Objectives: To examine the practices and demographics of a population of psychedelic microdosers – including their psychiatric diagnoses, prescription medications, and recreational substance use patterns – to develop a foundation on which to conduct future clinical research. Methods: Participants ( n = 909; M age = 26.9, SD = 8.6; male = 83.2%; White/European = 79.1%) recruited primarily from the online forum Reddit completed an anonymous online survey. Respondents who reported using LSD, psilocybin, or both for microdosing were grouped and compared with non-microdosing respondents using exploratory odds ratio testing on demographic variables, rates of psychiatric diagnoses, and past-year recreational substance use. Results: Of microdosers, most reported using LSD (59.3%; M dose = 13 mcg, or 11.3% of one tab) or psilocybin (25.9%; M dose = 0.3 g of dried psilocybin mushrooms) on a one-day-on, two-days-off schedule. Compared with non-microdosers, microdosers were significantly less likely to report a history of substance use disorders (SUDs; OR = 0.17 (95% CI: 0.05–0.56)) or anxiety disorders (OR = 0.61 (95% CI: 0.41–0.91)). Microdosers were also more likely to report recent recreational substance use compared with non-microdosers (OR = 5.2 (95% CI: 2.7–10.8)). Conclusions: Well-designed randomized controlled trials are needed to evaluate the safety and tolerability of this practice in clinical populations and to test claims about potential benefits.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".