Impact of antiretroviral therapy on fertility desires among HIV-infected persons in rural Uganda
Bibliographic record
Abstract
BACKGROUND: Little is known about the fertility desires of HIV infected individuals on highly active antiretroviral therapy (HAART). In order to contribute more knowledge to this topic we conducted a study to determine if HIV-infected persons on HAART have different fertility desires compared to persons not on HAART, and if the knowledge about HIV transmission from mother-to-child is different in the two groups. METHODS: The study was a cross-sectional survey comparing two groups of HIV-positive participants: those who were on HAART and those who were not. Semi-structured interviews were conducted with 199 HIV patients living in a rural area of western Uganda. The desire for future children was measured by the question in the questionnaire "Do you want more children in future." The respondents' HAART status was derived from the interviews and verified using health records. Descriptive, bivariate and multivariate methods were used to analyze the relationship between HAART treatment status and the desire for future children. RESULTS: Results from the multivariate logistic regression model indicated an adjusted odds ratio (OR) of 1.08 (95% CI 0.40-2.90) for those on HAART wanting more children (crude OR 1.86, 95% CI 0.82-4.21). Statistically significant predictors for desiring more children were younger age, having a higher number of living children and male sex. Knowledge of the risks for mother-to-child-transmission of HIV was similar in both groups. CONCLUSIONS: The conclusions from this study are that the HAART treatment status of HIV patients did not influence the desire for children. The non-significant association between the desire for more children and the HAART treatment status could be caused by a lack of knowledge in HIV-infected persons/couples about the positive impact of HAART in reducing HIV transmission from mother-to-child. We recommend that the health care system ensures proper training of staff and appropriate communication to those living with HIV as well as to the general community.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".