Use of withdrawal management services among people who use illicit drugs in Vancouver, Canada
Bibliographic record
Abstract
BACKGROUND: For many individuals with substance use disorders, the entry point for addiction treatment can be through withdrawal management (e.g. detoxification) services. However, little is known about the factors that predict withdrawal management service use among people who use illicit drugs (PWUD). Using data derived from two prospective cohorts of PWUD, we conducted a longitudinal data analysis of factors associated with use of withdrawal management services. METHODS: Individuals participating in two cohorts of PWUD were prospectively followed between December 2005 and May 2016 in Vancouver, Canada. Bivariate and multivariate generalized estimating equations were used to examine factors associated with use of withdrawal management services. RESULTS: Out of a total of 2001 participants, 339 (16.9%) individuals reported having been to a withdrawal management centre in the previous 6 months at some point during the study period. In multivariate analyses, male sex (adjusted odds ratio [AOR]: 1.62, 95% Confidence Interval [CI]: 1.17-2.24), homelessness (AOR: 1.86, 95% CI: 1.45-2.38), binge use of any substance (AOR: 1.34, 95% CI: 1.08-1.67), having attended a supervised injection facility (AOR: 1.66, 95% CI: 1.3-2.11), and having accessed other addiction medicine treatment or supports (other than withdrawal management services or opioid agonist therapy; AOR: 3.34, 95% CI: 2.64-4.22) were positively associated with having accessed withdrawal management services, whereas older age (AOR: 0.81, 95% CI: 0.7-0.94) was negatively associated with the outcome. CONCLUSIONS: This study identified specific factors associated with accessing withdrawal management services. Current evidence suggests a need to re-examine the provision of withdrawal management services. Consideration needs to be given to redesigning access to care and bridging to evidence-based addiction treatment, particularly for highly vulnerable subpopulations, identified in this study as females and older people.
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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 | 0.000 |
| 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 | 0.001 |
| 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".