Lifetime and past-month substance use and injection among street-based female sex workers in Iran
Bibliographic record
Abstract
BACKGROUND: Street-based female sex workers (FSWs) are highly at risk of HIV and other harms associated with sex work. We assessed the prevalence of non-injection and injection drug use and their associated factors among street-based FSWs in Iran. METHODS: We recruited 898 FSWs from 414 venues across 19 major cities in Iran between October 2016 and March 2017. Correlates of lifetime and past-month non-injection and injection drug use were assessed through multivariable logistic regression models. Adjusted odds ratios (AOR) and 95% confidence intervals (CI) were reported. RESULTS: Lifetime and past-month non-injection drug use were reported by 60.3% (95% CI 51, 84) and 47.2% (95% CI 38, 67) of FSWs, respectively. The prevalence of lifetime and past-month injection drug use were 8.6% (95% CI 6.9, 10.7) and 3.7% (95% CI 2.6, 5.2), respectively. Recent non-injection drug use was associated with divorced marital status (AOR 2.00, 95% CI 1.07, 3.74), temporary marriage (AOR 4.31 [1.79, 10.40]), had > 30 clients per month (AOR 2.76 [1.29, 5.90]), ever alcohol use (AOR 3.03 [1.92, 6.79]), and history of incarceration (AOR 7.65 [3.89, 15.30]). Similarly, lifetime injection drug use was associated with ever alcohol use (AOR 2.74 [1.20-6.20]), ever incarceration (AOR 5.06 [2.48-10.28]), and ever group sex (AOR 2.44 [1.21-4.92]). CONCLUSIONS: Non-injection and injection drug use are prevalent among street-based FSWs in Iran. Further prevention programs are needed to address and reduce harms associated with drug use among this vulnerable population in Iran.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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".