A pilot study on risk and protective factors for opioid overdose among people who use street fentanyl during the COVID-19 pandemic
Bibliographic record
Abstract
North America is in the midst of an opioid overdose epidemic. British Columbia has been particularly impacted by the epidemic, as over 7,000 have died from illicit drug overdoses since the crisis was declared a public health emergency in 2016. These deaths have largely been fueled by the widespread prevalence of illicitly manufactured fentanyl. Moreover, the crisis has now been exacerbated by the COVID-19 pandemic, as several jurisdictions have experienced record numbers of overdose deaths in 2020. We undertook a narrative review to describe the risk and protective factors for opioid overdose examined in the current literature. While a range of factors have been studied, it remains unclear how factors previously identified in those using heroin, and how novel fentanyl-related factors are influencing the risk of overdose in those using fentanyl. We thereby conducted a cross-sectional pilot study to investigate the risk and protective factors for non-fatal opioid overdose among 36 participants using street fentanyl during the COVID-19 pandemic. We found that 86.1% reported the intentional use of fentanyl, and 47.2% reported having overdosed in the past six months. These findings add to the growing evidence base that more individuals are intentionally using fentanyl, rather than unintentionally using it. Gender, history of opioid overdose, and suicidal ideation were identified as risk factors for recent overdose. Route of administration, receiving opioid agonist treatment, and receiving safe supply were not significantly associated with overdose. This suggests that risk and protective factors previously identified in individuals who use heroin should be re-examined as their contributions to overdose risk may be different in individuals who use fentanyl. Novel factors related to fentanyl and the pandemic should be further investigated to examine their roles in overdose risk. Future studies in this urgently needed area of research will improve the identification of individuals at risk of overdose, and inform the development of tailored interventions and policies to improve health outcomes in this vulnerable population.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".