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Record W4391160381 · doi:10.1080/09540121.2024.2307391

The path towards an HIV-free generation: engaging adolescent boys and young men (ABYM) in sub-Saharan Africa from lessons learned and future directions

2024· article· en· W4391160381 on OpenAlexaff
Tawanda Makusha, Lesley Gittings

Bibliographic record

VenueAIDS Care · 2024
Typearticle
Languageen
FieldHealth Professions
TopicAdolescent Sexual and Reproductive Health
Canadian institutionsWestern University
Fundersnot available
KeywordsHuman immunodeficiency virus (HIV)Path (computing)PsychologyDevelopmental psychologyEconomic growthPolitical scienceMedicineVirologyComputer scienceEconomics

Abstract

fetched live from OpenAlex

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.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.640
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.094
GPT teacher head0.390
Teacher spread0.296 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations9
Published2024
Admission routes1
Has abstractyes

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