Bibliographic record
Abstract
BACKGROUND: Documenting trends in condom use and exploring factors associated with their utilization are important for broadening the information base for the design of HIV intervention programs. This paper aims to document Uganda's nationwide trends in condom use from 1995 to 2006 and seeks to understand some of the socio-demographic variables that may be associated with their use, using Uganda Demographic Health Surveys (UDHSs). METHOD: Data from UDHSs conducted in 1995, 2000/2001 and 2006 were analyzed. Socio-demographic variables as well as 'survey year' were selected to assess their interaction with condom use. Multivariate regression analyses were performed. Odds ratios and confidence intervals were computed. RESULTS: Socio-demographic factors such as being male and living in an urban setting were significantly associated with an increased likelihood of reported use of condoms. All results indicated a far greater increase in condom use between 1995 and 2000/2001 than between 2000/2001 and 2006. CONCLUSION: Policies need to intensify condom use campaigns especially among women and rural populations. The wane in increase in condom use between 2000/2001 and 2006 may be due to the large-scale influx of antiretrovirals (starting in 2004) which may be lowering the anxiety associated with the social construct of HIV/AIDS.
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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 | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".