Illicit drug use and injection practices among drug users on methadone and buprenorphine maintenance treatment in France
Bibliographic record
Abstract
AIMS: To evaluate the associations between methadone and high-dose buprenorphine maintenance treatment and illicit drug use and injection among drug users in France. DESIGN: A cross-sectional study. Data were gathered using a questionnaire administered containing closed-ended questions. SETTING: Drug dependence clinics (DDC) and general practitioners' (GPs) offices in three French cities. PARTICIPANTS: Drug users undergoing maintenance treatment with methadone (n = 197) and buprenorphine (n = 142). MEASUREMENTS: Interviews covered the use of illicit drugs (heroin, cocaine or crack) and injection practices (illicit drugs and/or substitution drugs) during the last month, current treatment modalities, socio-demographic and health characteristics. Bivariate analysis and multivariate logistic regressions were conducted. FINDINGS: Overall, 35.4% of respondents (34.5% in the methadone group, 36.6% in the buprenorphine group, P= 0.69) had used at least one illicit drug, 25.7% reported having injected drugs and 15.3% had injected the substitution drug. Injection was more common among buprenorphine-maintained individuals (40.1%) than among users on methadone (15.2%) (P < 0.01). Multivariate analyses indicate that the type of substitution drug (buprenorphine versus methadone) was not associated with illicit drug use (OR = 1.1; 95% CI = 0.7-1.8). In the buprenorphine group, injection was related independently to social situation, as measured by housing (unstable versus stable housing, OR = 4.3; 95% CI = 1.6-11.5), but this was not the case in the methadone group. The risk of injection increased with buprenorphine dosage (high/low dosage OR = 6.2; 95% CI = 2.0-19.7), but this association was not observed in the methadone group. CONCLUSION: Further studies comparing the benefits of these two types of treatment should be carried out, taking outcomes such as physical health, mental health and social functioning into consideration.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".