“It gives you a road map of what to do to solve your problems”: acceptability of a combination HIV prevention intervention among adolescent girls in Uganda
Bibliographic record
Abstract
BACKGROUND: The HIV burden remains a critical public health concern and adolescent girls are at significantly higher risk compared to the general adult population. Similar to other sub-Saharan African countries, Uganda reports high HIV prevalence among adolescent girls and young women. Yet, both evidence-based HIV prevention interventions and their acceptability among adolescent girls have not been widely studied. In this study, we examined the acceptability of the Suubi4Her intervention, an evidence-based combination intervention aimed at reducing HIV risk among adolescent girls in Uganda. METHODS: We conducted semi-structured in-depth interviews with 25 adolescent girls upon intervention completion to explore their experiences with the Suubi4Her intervention that was tested in a clinical trial in Uganda (2017-2023). Specifically, we explored their decision-making process for participating in the intervention, experiences with program attendance, and their feedback on specific intervention characteristics. Informed by the Theoretical Framework of Acceptability, the data were analyzed using thematic analysis. RESULTS: The main motivation for participation was access to health-related information, including information on STIs, HIV, and pregnancy as well as information on banking, saving, and income-generating activities. Though many participants did not have any initial concerns, mistrust of programs, initial paperwork, caregiver's ability to commit time, concerns about ability to save, and HIV/STI and pregnancy testing were raised by some participants. Facilitators to session attendance included motivation to learn information, caregiver commitment, reminder calls, and incentives received for participation. The main challenges included household responsibilities and obligations, difficulty raising transport money, and weather challenges. Adolescent girls appreciated the group format and found the location and times of the sessions convenient. They also found the content relevant to their needs and noted positive changes in their families. CONCLUSIONS: The results showed high intervention acceptability among adolescent girls. These findings have important programmatic and policy implications in Uganda, especially given the higher HIV prevalence among adolescent girls in the country. TRIAL REGISTRATION: NCT03307226 (Registered: 10/11/17).
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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 | 0.013 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| 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".