Correlates of contraceptive use among HIVdiscordant couples in Kenya
Bibliographic record
Abstract
Despite risks of HIV transmission to infants born of the HIV positive women, contraceptive use is uncommon among women in HIV discordant partnerships. The aim of this study was to determine the factors associated with contraceptive use in a clinical trial cohort of HIV serodiscordant couples based in Thika and Eldoret, Kenya. Data were analyzed from 481 HIV discordant couples enrolled in the Partners in Prevention HSV/HIV Transmission Study at the Thika and Eldoret sites. The primary study outcome was self-reported use of contraception other than condoms. Using a marginal longitudinal logistic model based on generalized estimating equations (GEE) approach we assessed the association of various demographic and behavioral factors with contraceptive use. At baseline the prevalence of non barrier contraceptive use among HIV positive and negative women was 24.3% and 25.7%, respectively. At month 12 of follow-up, the prevalence of contraceptive use was 44.4% among the HIV positive and 26% among the HIV negative women while at month 24, the prevalence of contraceptive use was 38.6% among the HIV positive and 18.2% among the HIV negative women. HIV positive women were more likely to report using contraception than HIV negative women (odds ratio (OR) 1.61 95% confidence interval (CI) 1.04-2.47). Additionally, being married (OR 2.4, 95% CI 1.2-5.0), attending Thika site clinic (OR 6.1, 95% CI 4.2-9.0), and having two or more children (OR 1.9, 95% CI 1.3-2.8) were significantly associated with use of non barrier contraceptives. Future programs should focus on interventions to increase contraceptive use among HIV serodiscordant couples, with a special emphasis on HIV negative women, unmarried women and women with few children.
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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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".