Association between mass media exposure and HIV testing uptake in Cameroon
Bibliographic record
Abstract
In sub-Saharan African countries, mass media is critical in disseminating health information, including the need for HIV testing. Yet, in Cameroon, there is a dearth of studies examining how exposure to mass media is effective in the uptake of HIV testing. Using the 2018 Cameroon Demographic and Health Survey, we examined the association between exposure to mass media and HIV testing among sexually active women (n = 12,619) and men (n = 5,607). Our findings revealed a generally low uptake of HIV testing although more women (78%) have ever tested for HIV compared to men (67%). Adjusting for demographic, socioeconomic, and psychosocial factors, we found for both women and men their exposure at least once a week to the Internet (aOR = 1.57, p<0.001 for women; aOR = 1.76, p<0.001 for men), print media (aOR = 1.59, p<0.05 for women; aOR = 2.04, p<0.001 for men), radio (aOR = 1.34, p<0.01 for women; aOR = 1.57, p<0.001 for men), and television (aOR = 1.74, p<0.001 for women; aOR = 1.94, p<0.001 for men) was significantly associated with a higher likelihood of testing for HIV compared to their counterparts with no exposure at all. Our findings underscore the importance of further integrating mass media in HIV messaging in Cameroon as the country aims to achieve UNAIDS target 95-95-95 by 2023.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".