Microdosing psychedelics: Demographics, practices, and psychiatric comorbidities
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
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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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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 it