Drug checking in the fentanyl era: Utilization and interest among people who inject drugs in San Diego, California
Bibliographic record
Abstract
BACKGROUND: In North America, overdose rates have steeply risen over the past five years, largely due to the ubiquity of illicitly manufactured fentanyls in the drug supply. Drug checking services (DCS) represent a promising harm reduction strategy and characterizing experiences of use and interest among people who inject drugs (PWID) is a priority. METHODS: Between February-October 2022, PWID participating in a cohort study in San Diego, CA and Tijuana, Mexico completed structured surveys including questions about DCS, socio-demographics and substance use behaviors. We used Poisson regression to assess factors associated with lifetime DCS use and characterized experiences with DCS and interest in free access to DCS. RESULTS: Of 426 PWID, 72% were male, 59% Latinx, 79% were experiencing homelessness and 56% ever experienced a nonfatal overdose. One third had heard of DCS, of whom 57% had ever used them. Among the latter, most (98%) reported using fentanyl test strips (FTS) the last time they used DCS; 66% did so less than once per month. In the last six months, respondents used FTS to check methamphetamine (48%), heroin (30%) or fentanyl (29%). Relative to White/non-Latinx PWID, those who were non-White/Latinx were significantly less likely to have used DCS [adjusted risk ratio (aRR): 0.22; 95% CI: 0.10, 0.47), as were PWID experiencing homelessness (aRR:0.45; 95% CI: 0.28, 0.72). However, a significant interaction indicated that non-White/Latinx syringe service program (SSP) clients were more likely to have used DCS than non-SSP clients (aRR: 2.79; CI: 1.09, 7.2). Among all PWID, 44% expressed interest in free access to FTS, while 84% (of 196 PWID) expressed interest in advanced spectrometry DCS to identify and quantify multiple substances. CONCLUSIONS: Our findings highlight low rates of DCS awareness and utilization, inequities by race/ethnicity and housing situation, high interest in advanced spectrometry DCS versus FTS, and the potential role of SSPs in improving access to DCS, especially among racial/ethnic minorities.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 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) | 0.000 | 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".