The Effect of a Life-Stage Based Intervention on Depression in Youth Living with HIV in Kenya and Uganda: Results from the SEARCH-Youth Trial
Bibliographic record
Abstract
Depression among adolescents and young adults with HIV affects both their wellbeing and clinical care outcomes. Integrated care models are needed. We hypothesized that the SEARCH-Youth intervention, a life-stage-based care model that improved viral suppression, would reduce depressive symptoms as compared to the standard of care. We conducted a mixed-methods study of youth with HIV aged 15-24 years in SEARCH-Youth, a cluster-randomized trial in rural Uganda and Kenya (NCT03848728). Depression was assessed cross-sectionally with the PHQ-9 screening tool and compared by arm using targeted minimum loss-based estimation. In-depth semi-structured interviews with young participants, family members, and providers were analyzed using a modified framework of select codes pertaining to depression. We surveyed 1,234 participants (median age 21 years, 80% female). Having any depressive symptoms was less common in the intervention arm (53%) compared to the control (73%), representing a 28% risk reduction (risk ratio: 0.72; CI: 0.59-0.89). Predictors of at least mild depression included pressure to have sex, physical threats, and recent major life events. Longitudinal qualitative research among 113 participants found that supportive counseling from providers helped patients build confidence and coping skills. Integrated models of care that address social threats, adverse life events, and social support can be used to reduce depression among adolescents and young adults with HIV.
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 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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".