Contraceptive counseling experiences among women attending HIV care and treatment centers: A national survey in Kenya
Bibliographic record
Abstract
OBJECTIVES: To characterize contraceptive counseling experiences among women living with HIV (WLWH) receiving HIV care in Kenya. STUDY DESIGN: Sexually active, WLWH aged 15 to 49 years were purposively sampled from 109 high-volume HIV Care and Treatment Centers in Kenya between June and September 2016. Cross-sectional surveys were administered to enroll women on a tablet using Open Data Kit. Poisson generalized linear regression models adjusted for facility-level clustering were used to examine cofactors for receiving family planning (FP) counseling with a provider. RESULTS: Overall, 4805 WLWH were enrolled, 60% reported they received FP counseling during the last year, 72% of whom reported they were counseled about benefits of birth spacing and limiting. Most women who received FP counseling were married (64%) and discussed FP with their partner (78%). Use of FP in the last month (adjusted Prevalence Ratio [aPR] = 1.74, 95% confidence interval [CI]: 1.41-2.15, p < 0.001), desire for children in >2 years (aPR = 1.18, 95% CI: 1.09-1.28, p < 0.001), and concern about contraceptive side-effects (aPR = 1.13, 95% CI 1.02-1.25, p < 0.05) were significantly higher among WLWH who received FP counseling compared to those that did not. CONCLUSIONS: Over one-third of WLWH did not receiving FP counseling with an HIV care provider during the last year, and counseling was more commonly reported among women who were using FP or desired children in >2 years. IMPLICATIONS: There are missed opportunities for FP counseling in HIV care. FP integration in HIV care could improve FP access and birth spacing or limiting among WLWH.
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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 | 0.000 | 0.001 |
| 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) | 0.002 | 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".