Understanding intentionality of fentanyl use and drug overdose risk: Findings from a mixed methods study of people who inject drugs in New York City
Bibliographic record
Abstract
BACKGROUND: As the proportion of drug overdose deaths involving fentanyl continues to increase in the US, monitoring exposure to and possible changes in intention to use fentanyl among people who use drugs (PWUD) is of great public health importance. This mixed methods study examines intentionality of fentanyl use among persons who inject drugs (PWID) in New York City during a period of unprecedently high rates of drug overdose mortality. METHODS: Between October 2021 and December 2022, N = 313 PWID were enrolled in a cross-sectional study that included a survey and urine toxicology screening. A subset of N = 162 PWID also participated in an in-depth interview (IDI) examining drug use patterns, including fentanyl use and experiences with drug overdose. RESULTS: 83% of PWID were urine-toxicology positive for fentanyl, though only 18% reported recent intentional fentanyl use. Intentionality of fentanyl use was associated with being younger, white, increased drug use frequency, recent overdose (OD), recent stimulant use, among other characteristics. Qualitative findings suggest PWID tolerance to fentanyl may be increasing, which could result in an increased preference for fentanyl. Concern about overdose was common with nearly all PWID using overdose prevention strategies to avoid it. CONCLUSION: The findings from this study demonstrate a high prevalence of fentanyl use among PWID in NYC, despite an expressed preference for heroin. Our results suggest that the pervasiveness of fentanyl may be increasing fentanyl use and tolerance, which may contribute to an increased risk for drug overdose. Expanding access to existing evidence-based interventions such as naloxone and medications for opioid use disorder is necessary to reduce overdose mortality. Further, exploring the implementation of additional novel strategies to reduce the risk of drug overdose should be considered, including other forms of opioid maintenance treatment and expansion and government support for overdose prevention centers.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.000 |
| 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".