Microdosing as a response to the meaning crisis
Bibliographic record
Abstract
Background: The use of psychedelic substances like LSD and magic mushrooms in research and to treat mental health conditions has been increasing in the last decade. In particular, the practice of microdosing – using sub-hallucinogenic amounts of psychedelics – has been increasing (Anderson et al., 2019), but large-scale systemic qualitative analyses are still scant.Aims: This study attempted to recognize emergent themes in qualitative reports regarding the experience of microdosing so as to enrich the theoretical landscape in psychedelics research and propose future research directions for both basic and clinical research.Methods: This study used qualitative analysis to analyze free-text responses from individuals who participated in an online survey disseminated on various social media platforms. Participants had reported microdosing at least once in the past year.Results: Data from 118 informative responses suggested four main emergent themes: reasons for microdosing, the practice of microdosing, outcomes linked to microdosing, and meta-commentary about microdosing. Participants mostly reported microdosing for clinical reasons and to improve productivity, and mentioned that the practice is often challenging due to unknown optimal dosing regimen. The outcomes of microdosing varied widely between strong endorsement of the practice and disappointment at the lack of effect. Meta-commentary included warning against overexcitement with the practice. We couch our findings in meaning-making theory and propose that, even at low doses, psychedelic substances can provide a sense of meaning currently lacking in Western culture.Conclusion: Our results suggest that there many of the reported benefits occur regardless of motivation to microdose and are likely due to the enhanced psychological flexibility and sense of connectedness made possible due to the use of psychedelics. Double-blind, placebo controlled experiments are required in order to substantiate these reports.
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How this classification was reachedexpand
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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.003 |
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 teacher head, 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".