High-Yield HIV Testing, Facilitated Linkage to Care, and Prevention for Female Youth in Kenya (GIRLS Study): Implementation Science Protocol for a Priority Population
Bibliographic record
Abstract
BACKGROUND: Sub-Saharan Africa is the region with the highest HIV burden. Adolescent girls and young women (AGYW) in the age range of 15 to 24 years are twice as likely as their male peers to be infected, making females in sub-Saharan Africa the most at-risk group for HIV infection. It is therefore critical to prioritize access to HIV testing, prevention, and treatment for this vulnerable population. OBJECTIVE: Using an implementation science framework, the purpose of this research protocol was to describe the approaches we propose to optimize engagement of AGYW in both the HIV prevention and care continuum and to determine the recruitment and testing strategies that identify the highest proportion of previously undiagnosed HIV infections. METHODS: We will compare two seek recruitment strategies, three test strategies, and pilot adaptive linkage to care interventions (sequential multiple assignment randomized trial [SMART] design) among AGYW in the age range of 15 to 24 years in Homa Bay County, western Kenya. AGYW will be recruited in the home or community-based setting and offered three testing options: oral fluid HIV self-testing, staff-aided rapid HIV testing, or referral to a health care facility for standard HIV testing services. Newly diagnosed AGYW with HIV will be enrolled in the SMART trial pilot to determine the most effective way to support initial linkage to care after a positive diagnosis. They will be randomized to standard referral (counseling and a referral note) or standard referral plus SMS text message (short message service, SMS); those not linked to care within 2 weeks will be rerandomized to receive an additional SMS text message or a one-time financial incentive (approximately US $4). We will also evaluate a primary prevention messaging intervention to support identified high-risk HIV-negative AGYW to reduce their HIV risk and adhere to HIV retesting recommendations. We will also conduct analyses to determine the incremental cost-effectiveness of the seek, testing and linkage interventions. RESULTS: We expect to enroll 1200 participants overall, with a random selection of 100 high-risk HIV-negative AGYW for the SMS prevention intervention (HIV-negative cohort) and approximately 108 AGYW who are living with HIV for the SMART design pilot of adaptive linkage to care interventions (HIV-positive cohort). We anticipate that the linkage to care interventions will be feasible and acceptable to implement. Lastly, the use of SMS text messages to engage participants will provide pilot data to the Kenyan government currently exploring a national platform to track and support linkage, adherence to treatment, retention, and prevention interventions for improved outcomes. CONCLUSIONS: Lessons learned will inform best approaches to identify new HIV diagnoses to increase AGYW's uptake of HIV prevention, testing, and linkage to care services in a high HIV-burden African setting. TRIAL REGISTRATION: ClinicalTrials.gov NCT02735642; https://clinicaltrials.gov/ct2/show/NCT02735642 (Archived by WebCite at http://www.webcitation.org/6vgLLHLC9).
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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 | 0.095 | 0.054 |
| Meta-epidemiology (narrow) | 0.004 | 0.004 |
| Meta-epidemiology (broad) | 0.004 | 0.005 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.005 | 0.005 |
| Research integrity | 0.007 | 0.008 |
| Insufficient payload (model declined to judge) | 0.058 | 0.009 |
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".