Contextual Parameters Associated with Positive and Negative Mental Health in Recreational Psychedelic Users
Bibliographic record
Abstract
Growing research exploring the utility of psychedelic substances suggests that they not only hold promise for clinical practice but may enhance mental health through recreational use as well. However, given the importance of set and setting for maximizing benefits and minimizing harms of drug use, it is important to develop a foundational understanding of the contextual factors associated with positive and negative mental health in psychedelic users. Accordingly, data were collected using an internet-based survey of psychedelic drug users (n = 511). Hierarchical regression analyses were used to explore to what degree life-time use, frequency of use, dose size, group use, intentions for use, and post-use integration predict mental health in psychedelic users. In particular, using psychedelics with high frequency and to cope with negative affect were found to predict negative mental health. Conversely, using psychedelics in a group setting, with self-expansive intentions, and integrating post-use were found to predict positive mental health. Findings suggest that recreational psychedelic use may either enhance or diminish mental health depending on the contextual parameters of use. Limitations and areas for further research are discussed.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".