Testing for amphetamine-type stimulant (ATS) use to ascertain validity of self-reported ATS use among young female sex workers in Cambodia
Bibliographic record
Abstract
OBJECTIVE: To assess concordance between self-reported amphetamine-type stimulant (ATS) use and toxicology results among young female sex workers (FSW) in Phnom Penh, Cambodia. METHODS: Cross-sectional data from the Young Women's Health Study-2 (YWHS-2), a prospective study of HIV and ATS use among young (15 to 29 years) FSW in Phnom Penh, Cambodia, was analyzed. The YWHS-2 assessed sociodemographic characteristics, HIV serology, HIV risk, and ATS use by self-report and urine toxicology testing at each quarterly visit, the second of which provided data for this assessment. Outcomes include sensitivity, specificity, positive- and negative predictive values (overall and stratified by age), sex-work setting, and HIV status. RESULTS: Among 200 women, prevalence of positive toxicology screening for ATS use was 14% (95% confidence interval [CI], 9.2, 18.9%) and concurrent prevalence of self-reported ATS was 15.5% (95% CI, 10.4, 20.6%). The sensitivity and specificity of self-reported ATS use compared to positive toxicology test results was 89.3% (25/28), and 96.5% (166/172), respectively. The positive predictive value of self-reported ATS use was 80.6% (25/31); the negative predictive value was 98.2% (166/169). Some differences in concordance between self-report and urine toxicology results were noted in analyses stratified by age group and sex-work setting but not by HIV status. CONCLUSION: Results indicate a high prevalence of ATS use among FSW in Phnom Penh, Cambodia, and high concordance between self-reported and toxicology-test confirmed ATS use.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".