Integrating Adolescent Mental Health into HIV Prevention and Treatment Programs: Can Implementation Science Pave the Path Forward?
Bibliographic record
Abstract
Adolescent mental health (AMH) is a critical driver of HIV outcomes, but is often overlooked in HIV research and programming. The implementation science Exploration, Preparation, Implementation, Sustainment (EPIS) framework informed development of a questionnaire that was sent to a global alliance of adolescent HIV researchers, providers, and implementors working in sub-Saharan Africa with the aim to (1) describe current AMH outcomes incorporated into HIV research within the alliance; (2) identify determinants (barriers/gaps) of integrating AMH into HIV research and care; and (3) describe current AMH screening and referral systems in adolescent HIV programs in sub-Saharan Africa. Respondents reported on fourteen named studies that included AMH outcomes in HIV research. Barriers to AMH integration in HIV research and care programs were explored with suggested implementation science strategies to achieve the goal of integrated and sustained mental health services within adolescent HIV programs.
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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 | 0.156 | 0.204 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.003 | 0.006 |
| Scholarly communication | 0.016 | 0.011 |
| Open science | 0.003 | 0.011 |
| Research integrity | 0.003 | 0.008 |
| Insufficient payload (model declined to judge) | 0.005 | 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".