A Comparison of Comprehensive HIV/AIDS Knowledge Among Women Across Seven Post-Soviet Countries
Bibliographic record
Abstract
INTRODUCTION: Post-Soviet countries of Eastern Europe and Central Asia have witnessed a recent growth of HIV infection through heterosexual transmission. Women's low levels of knowledge about HIV prevention and transmission methods have been found to account for the higher female-to-male ratio among cases infected through the heterosexual route. This cross national comparison study assessed comprehensive HIV/AIDS knowledge and its key determinants among women of seven post-Soviet countries and identified which countries face the highest levels of risk due to the low levels of HIV/AIDS awareness. METHODS: Study data were obtained from the third wave of the Multiple Indicator Cluster Surveys (MICS3) (conducted in 2005 and 2006), nationally representative samples of women aged 15-49 years. Data on HIV/AIDS knowledge were analyzed for women in Kazakhstan (N=14,310), Kyrgyzstan (N=6,493), Tajikistan (N=4,676), Uzbekistan (N=13,376), Belarus (N=5,884), Ukraine (N=6,066), and Georgia (N=7,727) using descriptive statistics and ordinary least squares (OLS) regressions. RESULTS: We found that the percentage of women who could correctly identify all five modes of HIV/AIDS transmission and prevention was highest in Eastern European countries of Belarus (34.98%) and Ukraine (31.67%). Across all countries, the strongest predictors of comprehensive HIV/AIDS knowledge were age, education, and region of residence. Marital status, area of residence (urban vs. rural), and household wealth were significant predictors for several countries. CONCLUSION: High rates of comprehensive HIV/AIDS knowledge were found among women of Belarus and Ukraine. To reduce the spread of HIV in the region, programs promoting comprehensive HIV/AIDS knowledge for women of younger ages and with lower education are recommended.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".