HIV and mental health among young people in low-resource contexts in Southeast Asia: A qualitative investigation
Bibliographic record
Abstract
Young people aged 15−24 years comprise one-fourth of incident HIV infections in Southeast Asia. Given the high prevalence and impact of mental health issues among young people, we explored intersections of HIV and mental health, with a focus on adolescent and young key populations (AYKP) in Indonesia, the Philippines, Thailand, and Vietnam. Sixteen focus group discussions (4/country) with young people (n = 132; 16−24 years) and 41 key informant interviews with multisectoral HIV experts explored young people's lived experiences and unmet needs, existing programmes, and strategic directions for local and regional HIV responses. Cross-cutting challenges emerged in healthcare, family, school, and peer domains amid fragmented and under-resourced HIV and mental health services in socio-politically fraught environments. We identified strategic opportunities and initiatives in development and integration of youth-friendly HIV and mental health services; programmes to promote parent–adolescent communication about sex and HIV; and teacher training and resources to advance HIV and mental health awareness, serve as first-responders, and provide community referrals. Youth-led peer education programmes and LGBT-networks were central to the HIV response—promoting HIV prevention, sexual health, and mental health awareness for young people, and resilience and socioeconomic empowerment of peer educators themselves—thereby transforming sociocultural and political contexts of vulnerability.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".