Myths and misconceptions about HIV transmission in Ghana: what are the drivers?
Bibliographic record
Abstract
Biomedical and social cognitive models driving HIV preventive activities in sub-Saharan Africa are mostly premised on factual and accurate knowledge of the disease. While knowledge about HIV exists in most parts of Africa, there is widespread belief in myths that often contradict and undermine preventive efforts. Using the 2008 Demographic and Health Survey and applying logit models, we examined what influences belief in myths and misconceptions surrounding HIV transmission among Ghanaian men and women. Results indicate that respondents with high knowledge of how HIV may be transmitted had lower odds of endorsing myths about the disease. Compared to the less educated and poorer Ghanaians, educated and wealthier Ghanaians were less likely to endorse myths about HIV. Also, compared to the Akan people, respondents identifying with other ethnic groups were significantly less likely to endorse myths. The findings suggest that policy makers provide accurate information about how the disease is spread to counter myths surrounding HIV transmission.
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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 | 0.005 | 0.027 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".