Race, Ethnic, and Sex Differences in Prevalence of and Trends in Hallucinogen Consumption Among Lifetime Users in the United States Between 2015 and 2019
Bibliographic record
Abstract
Background The current study is one of the first to examine race, ethnic, and sex differences in the prevalence of and trends in hallucinogen use among lifetime users in the United States. Methods Data came from the 2015–2019 National Survey on Drug Use and Health and included respondent's reporting ever-using hallucinogens ( n = 41,060; female = 40.4%). Descriptive and multinomial logistic regression analyses were conducted in Stata. Results Highest prevalence of past year hallucinogen use was among Asian females (35.06%), which was two-or-more times larger than prevalence of past year use among White males/females and Native American males. More than half of White males/females, Multiracial males, and Hispanic males reported had ever-used psilocybin or LSD, whereas less than one-quarter of Black males/females reported lifetime psilocybin use, and less than a third of Black females reported lifetime LSD use. Native American males had the lowest prevalence of lifetime MDMA use (17.62–33.30%) but had the highest lifetime prevalence of peyote use (40.37–53.24%). Pacific Islander males had the highest prevalence of lifetime mescaline use (28.27%), and lifetime DMT use was highest among Pacific Islander males/females (15.68–38.58%). Black, Asian, and Multiracial people had greater odds of past-year (ORs = 1.20–2.02; p s < 0.05) and past-month (ORs = 1.39–2.06; p s < 0.05) hallucinogen use compared to White people. Females had lower odds of past-year (OR = 0.79; p s < 0.05), past-month (OR = 0.78; p s < 0.05) hallucinogen use compared to males, except for lifetime use of MDMA (OR = 1.29; p s < 0.05). Conclusions These findings should inform public health initiatives regarding potential benefits and risks of hallucinogen use among racial/ethnic groups and women.
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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 | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 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".