Eating sweets without the wrapper: perceptions of HIV and sexually transmitted infections among street youth in western Kenya
Bibliographic record
Abstract
Street-connected youth in Kenya are a population potentially at risk of HIV transmission, yet little is known about their perceptions and experiences of sexually transmitted infections (STIs), despite their living in an HIV endemic region. We sought to elucidate the language and sociocultural factors rooted in street life that impact on street-connected young people's knowledge of and perceptions about the prevention and transmission of STIs, and their diagnosis and treatment, using qualitative methods in western Kenya. We conducted a total of 25 in-depth interviews and 5 focus-group discussions with 65 participants aged 11-24 years in Eldoret, Kenya. Thematic analysis was conducted and data were coded according to themes and patterns emergent until saturation was reached. In general, street-connected young people knew of STIs and some of the common symptoms associated with these infections. However, there were many misconceptions regarding transmission and prevention. Gender inequities were prominent, as the majority of men described women as individuals who spread STIs due to unhygienic practices, urination and multiple partners. Due to misconceptions, gender inequity and lack of access to youth-friendly healthcare there is an urgent need for community-based organisations and healthcare facilities to introduce or augment their adolescent sexual and reproductive health programmes for vulnerable young people.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".