Factors Associated With Increased Opioid Use During the COVID-19 Pandemic: A Prospective Study of Patients Enrolled in Opioid Agonist Treatment
Bibliographic record
Abstract
OBJECTIVES: The opioid use disorder (OUD) crisis in North America has become "an epidemic within a pandemic" in the context of the COVID-19 virus. We aimed to explore the association between the COVID-19 pandemic and changes in opioid use patterns among patients receiving treatment for OUD. METHODS: We used prospectively collected data from 456 patients attending 31 opioid agonist clinics across Ontario, Canada. All included participants underwent routine urine drug screens (UDSs) both before and after the onset of the COVID-19 pandemic. A paired sample t -test was used to compare the proportion of opioid-positive UDSs collected pre- and post-pandemic, and linear regression analysis was used to explore factors associated with this change. RESULTS: Participants had a mean age of 39.9 years (standard deviation = 10.9), 52%were male, and 81%were receivingmethadone treatment. The percentage of opioid-positive UDSs increased significantly during the pandemic, on average by 10.6% (95% confidence interval [CI] 8.17, 12.95, P < 0.001). Continued opioid use before the pandemic was associated with 9.43% increase, on average, in the percentage of opioid-positive UDSs during the pandemic (95% CI 3.79, 15.07). Self-reported past-month cocaine (adjusted betacoefficient 6.83, 95% CI 0.92, 12.73) and amphetamine (adjusted beta-coefficient 13.13, 95% CI 5.15, 21.1) use at study entry were also associated with increases in opioid-positive UDSs. CONCLUSIONS: Increased opioid use is one measure of the negative impact the COVID-19 pandemic has had on individuals with OUD, an already marginalized population. Understanding factors associated with worse outcomes is essential to ensuring that treatment programs appropriately adapt to better serve this population during the pandemic.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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".