Structural determinants of dual contraceptive use among female sex workers in Gulu, northern Uganda
Bibliographic record
Abstract
OBJECTIVE: To describe the characteristics of female sex workers (FSWs) who do and do not use dual contraceptives (i.e. male condoms plus a non-barrier method) in Gulu, northern Uganda. METHODS: The present analysis was based on data gathered as part of a questionnaire-based, cross-sectional study conducted between May 2011 and January 2012. FSWs aged 14 years or older were recruited through peer-led or sex worker-led outreach and community-based services. Logistic regression was used to identify correlates of dual contraceptive use. RESULTS: Among the 400 FSWs who participated, 180 (45.0%) had ever used dual contraceptives. In the multivariate model, dual contraceptive use was positively associated with older age (adjusted odds ratio [AOR] 1.09, 95% confidence interval [CI] 1.04-1.15; P=0.001), prior unintended pregnancy (AOR 1.53, 95% CI 1.01-2.34; P=0.046), and HIV testing (AOR 5.22, 95% CI 1.75-15.57; P=0.003). Having to rush sexual negotiations owing to police presence was negatively associated with dual contraceptive use (AOR 0.65, 95% CI 0.42-1.00; P=0.050). CONCLUSION: Although a history of unintended pregnancy and accessing HIV testing might promote contraceptive use, criminalized work environments continue to pose barriers to uptake of sexual and reproductive health services among FSWs in post-conflict northern Uganda. Integrated links between HIV and sexual health programs could support contraceptive uptake among FSWs.
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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 | 0.001 | 0.003 |
| 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 | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".