Persistent misconceptions about HIV transmission among males and females in Malawi
Bibliographic record
Abstract
BACKGROUND: The prevalence of HIV in Malawi is one of the highest in sub-Saharan Africa, and misconceptions about its mode of transmission are considered a major contributor to the continued spread of the virus. METHODS: Using the 2010 Malawi Demographic and Health Survey, the current study explored factors associated with misconceptions about HIV transmission among males and females. RESULTS: We found that higher levels of ABC prevention knowledge were associated with lower likelihood of endorsing misconceptions among females and males (OR = 0.85, p < 0.001; OR = 0.85, p < 0.001, respectively). Compared to those in the Northern region, both females and males in the Central (OR = 0.54, p < 0.001; OR = 0.53, p < 0.001, respectively) and Southern regions (OR = 0.49, p < 0.001; OR = 0.43, p < 0.001, respectively) were less likely to endorse misconceptions about HIV transmission. Moreover, marital status and ethnicity were significant predictors of HIV transmission misconceptions among females but not among males. Also, household wealth quintiles, education, religion, and urban-rural residence were significantly associated with endorsing misconceptions about HIV transmission. CONCLUSION: Based on our findings, we recommend that education on HIV transmission in Malawi should integrate cultural and ethnic considerations of HIV/AIDS.
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 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 | 0.004 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".