Trends and correlates of discordant reporting of drug use among nightclub/festival attendees, 2019–2022
Bibliographic record
Abstract
Introduction People who attend nightclubs and festivals are known for high prevalence of party drug use, but more research is needed on underreporting in this population, in part because unintentional drug exposure through adulterated drug products is common. We examined the prevalence of drug use in this population, based both on self-reporting and on hair test results, with a focus on the detection of underreported use.Methods Adults entering nightclubs and festivals in New York City were asked about past-year drug use in 2019–2022 (n = 1,953), with 328 providing an analyzable hair sample for testing. We compared trends in self-reported drug use, drug positivity, and "corrected" prevalence, adjusting for unreported use, and delineated correlates of testing positive for ketamine and cocaine after not reporting use (discordant reporting).Results Of the 328 who provided a sample, cocaine and ketamine were the most frequently detected drugs (55.2% [n = 181] and 37.2% [n = 122], respectively), but these were also the two most underreported drugs, with 37.1% (n = 65) and 26.4% (n = 65), respectively, testing positive after not reporting use. Between 2019 and 2022, positivity decreased for cocaine, ketamine, 3,4-methylenedioxy-metamfetamine, and amfetamine, and underreported exposure to cocaine and ketamine also decreased (P < 0.05). Underreporting of the use of these drugs was common, but we also detected underreported exposure to ethylone, fentanyl, 3,4-methylenedioxyamfetamine, metamfetamine, and synthetic cannabinoids. Prevalence of discordant reporting of cocaine use was higher among those testing positive for ketamine exposure (adjusted prevalence ratio = 2.63; 95% CI: 1.48–4.69) and prevalence of discordant reporting of ketamine use was lower post-coronavirus disease caused by the SARS-CoV-2 virus (adjusted prevalence ratio = 0.39; 95% CI: 0.16–0.91) and among those reporting cocaine use (adjusted prevalence ratio = 0.53; 95% CI: 0.32–0.89).Discussion Underreporting of drug use was common, suggesting the need for researchers to better deduce intentional underreporting versus unknown drug exposure via adulterants.Conclusions Researchers should consider both self-report and toxicology results from biological samples when examining trends in use.
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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 | 0.006 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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 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".