How Does Exposure to Mass Media affect HIV Testing and HIV-Related Knowledge Among Adolescents? Evidence From Uganda
Bibliographic record
Abstract
Sexual and reproductive health remains one of the greatest challenges in developing countries. In Uganda, adolescents are the most vulnerable group of the population as far as HIV epidemic is concerned. Mass media awareness campaigns play a key role in promoting sexual and reproductive health among adolescents. Using Uganda’s 2016 Demographic Health Survey, we examine the causal effect of mass media exposure on the probability of adolescents getting an HIV test and their HIV-related knowledge. Our results suggest that the exposure to mass media increases both adolescents’ likelihood to get tested for HIV and their HIV-related knowledge score. In fact, we find that reading newspapers once a week increases the likelihood of an adolescent to test for HIV by 6.29 percentage points. Listening to radio once a week increases the probability to test for HIV by 4.57 percentage points. This effect increases to 6.56 percentage points when the adolescent listens to the radio more than once a week. Watching TV more than once a week increases adolescents’ probability to get tested for HIV by 8.57 percentage points. For HIV-related knowledge, we find that compared to adolescents who do not read newspapers at all, adolescents who read newspapers less than once a week and those who read newspapers at least once a week have a higher score of HIV-related knowledge of 9.12% and 9.64% respectively. Compared to adolescents who do not listen to radio at all, adolescents who listen to radio less than once a week have a higher (5.88%) score of HIV related knowledge. Moreover, listening to radio at least once a week increases the score of HIV-related knowledge by 5.52%. Hence, mass media awareness campaigns are important policies to promote HIV testing and HIV-related knowledge among adolescents in Uganda.
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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 | 0.004 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 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".