Inability to Access Addiction Treatment and Risk of HIV Infection Among Injection Drug Users
Bibliographic record
Abstract
It was recently found that 94% of the nearly $500 million allocated annually to Canada's illicit drug strategy has been spent on enforcement-based interventions. As a result, lack of funds for addiction treatment has meant demand for substance abuse treatment among illicit drug users has exceeded availability. This study evaluated whether injection drug users (IDUs) who reported being unable to access addiction treatment were at elevated risk of HIV infection. A prospective analysis was done of factors associated with syringe borrowing by baseline HIV-negative IDUs among participants enrolled in the Vancouver Injecting Drug Users Study (VIDUS). Since serial measures for each individual were available, variables potentially associated with syringe borrowing were evaluated using generalized estimating equations (GEEs) with logit link for binary outcomes. Overall, 1157 HIV-negative IDUs were enrolled into the VIDUS cohort between May 1996 and May 2002. Unsuccessful attempts to access addiction treatment were associated with reporting syringe borrowing during follow-up in both univariate (odds ratio 1.72; 95% CI 1.47-2.00; P<0.001) and in multivariate GEE analyses (adjusted odds ratio 1.29; 95% CI 1.09-1.53; P=0.003). Inability to access addiction treatment was independently associated with syringe borrowing among HIV-negative IDUs at risk for HIV infection. These findings suggest that the limited provision of addiction treatment may result in a major missed opportunity to reduce HIV transmission behavior among IDUs and that the expansion of addiction treatment services has major potential to reduce the substantial human and fiscal costs of HIV infection.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".