<p>Greater Pain Severity is Associated with Inability to Access Addiction Treatment Among a Cohort of People Who Use Drugs</p>
Bibliographic record
Abstract
Aim: Given that co-occurring pain is prevalent among people who use drugs (PWUD), we sought to explore the effect of pain severity on accessing addiction treatment. Methods: Data were derived from two prospective cohort studies of PWUD in Vancouver, Canada from June 2014 to May 2016. Multivariable generalized linear mixed-effects multiple regression (GLMM) analyses were used to investigate the association between average pain severity and self-reported inability to access addiction treatment. Results: Among 1348 PWUD, 136 (10.1%) reported being unable to access addiction treatment at least once over the study period. Individuals who reported being unable to access addiction treatment had a significantly higher median average pain severity score (median=5, IQR=0– 7) compared to individuals reporting no inability to access addiction treatment (median=3, IQR=0– 6, p =0.038). Greater pain severity was independently associated with higher odds of reporting inability to access addiction treatment (AOR: 1.75, 95%CI: 1.08– 2.82 for mild-moderate vs no pain; AOR: 1.98, 95%CI: 1.27– 3.09 for moderate-severe vs no pain). Conclusion: PWUD with greater pain severity may be at higher risk of being unable to access addiction treatment, or vice versa. While further research is needed to confirm causal associations, these data suggest that there may be underlying pathways or mechanisms through which pain may be associated with access to addiction treatment for PWUD. Keywords: pain, addiction, substance use, health services, opioid agonist treatment, methadone
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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 | 0.007 | 0.004 |
| 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 | 0.001 |
| 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".