The path towards an HIV-free generation: engaging adolescent boys and young men (ABYM) in sub-Saharan Africa from lessons learned and future directions
Bibliographic record
Abstract
This paper highlights the pressing need to address the HIV epidemic among adolescent boys and young men (ABYM) in sub-Saharan Africa. Despite progress in HIV prevention, ABYM still experience low diagnosis rates, treatment adherence, and linkage to care. The paper emphasizes ABYM's vulnerability due to societal norms, limited healthcare access, and economic pressures. It calls for gender-responsive interventions, including comprehensive sexual education, youth-friendly health services, community engagement, and targeted outreach. Comprehensive sexual education is pivotal in HIV prevention for ABYM, providing them with age-appropriate sexual health knowledge and safer sexual practices to reduce HIV incidence. Harmful masculine norms must be countered to promote respectful relationships, benefiting boys, men, and their partners. Inadequate access to youth-friendly health services hampers HIV prevention. Establishing spaces with confidential, non-judgmental care offering testing, counselling, circumcision, and provision of pre-exposure prophylaxis (PrEP) is essential, especially considering ABYM's unique clinic experiences. Engaging communities, leaders, educators, and peers combats stigma and discrimination. ABYM's input in intervention design, targeted outreach, and innovative technology enhances effectiveness of HIV prevention programmes. Economic factors should also be addressed. Comprehensive multi-sectoral interventions, including conditional cash transfers, effective for AGYW, could benefit ABYM. Addressing structural factors alongside behaviour change and social support is key.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".