Predictors of multiple sexual partnerships among women and men in two urban townships in Bhutan
Bibliographic record
Abstract
Introduction: Multiple sexual partnering is a known predictor for risk of STI and HIV transmission. This study explored the multiple sexual partnering and its predictors among people who visited public social venues (bars, restaurants, hotels, lodges, cafes, karaokes and discos) in Bhutan’s two largest townships of Thimphu and Phuntsholing. Methods: We interviewed 755 sexually active venue patrons from 102 randomly selected venues (56 in Thimphu, 46 in Phuntsholing) from a list of all venues identified as having sex workers or patrons seeking sexual partners. Both bivariate and multivariate analyses were carried out to characterize the predictors of multiple sexual partnering among 755 respondents who had previously had sex. Results: Of the 755 patrons, 46.09% had one sexual partner while the remaining 54.91% had multiple sex partners (greater than or equal to 2 sexual partners) in the 12 months preceding the study. Overall, 6.23% of respondents had received payment from someone at least once for sex; 34.61% of male respondents had paid someone at least once for sex. Nearly all patrons (97.72%) had heard about HIV/ AIDS. About one quarter (24.20%) felt that they were at risk of being infected with HIV, while 37.28% had taken an HIV test in the 12 months preceding the study. In multivariate analysis, males had higher odds of multiple sexual partners compared to females (OR =3.19, 95% CI 1.90-5.20). The odds of having multiple sexual partners was 2.24 (95% CI 1.30-3.90) times higher in those never married compared to those who were married/divorced or separated; multiple partnering increased with increasing age (OR = 1.07 per year, 95% CI 1.02-1.13). Between the townships of Phuentsholing and Thimphu, the odds of multiple sexual partnering did not vary. Conclusions: Venue patrons had a high prevalence of multiple sexual partnering and have the potential for creating sexual networks that could propagate wider transmission of infection, including to their monogamous partner. Targeting HIV prevention program to these groups of people in urban locations presents an opportunity to make a great impact in maintaining Bhutan’s current low HIV epidemic level.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| 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 | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".