Strategies to Treat and Prevent HIV in the United States for Adolescents and Young Adults: Protocol for a Mixed-Methods Study
Bibliographic record
Abstract
BACKGROUND: Over 20% of HIV diagnoses in the United States are among youth aged 12-24 years. Furthermore, youth have the lowest rates of uptake and adherence to antiretroviral (ARV) medications and are least aware of their HIV status. OBJECTIVE: Our objective was to design a set of interrelated studies to promote completion of each step of the HIV Prevention Continuum by uninfected youth at high risk (YHR), as well as completion of steps in the Treatment Continuum by youth living with HIV (YLH). METHODS: Gay, bisexual, and transgender youth; homeless youth; substance-abusing youth; youth with criminal justice contact; and youth with significant mental health challenges, particularly black and Latino individuals, are being recruited from 13 community-based organizations, clinics, drop-in centers, and shelters in Los Angeles and New Orleans. Youth are screened on the basis of self-reports and rapid diagnostic tests for HIV, drug use, and sexually transmitted infections and, then, triaged into one of 3 studies: (1) an observational cohort of YLH who have never received ARV medications and are then treated-half initially are in the acute infection period (n=36) and half with established HIV infection (n=36); (2) a randomized controlled trial (RCT) for YLH (N=220); and (3) an RCT for YHR (N=1340). Each study contrasts efficacy and costs of 3 interventions: an automated messaging and weekly monitoring program delivered via text messages (short message service, SMS); a peer support intervention delivered via social media forums; and coaching, delivered via text message (SMS), phone, and in-person or telehealth contacts. The primary outcomes are assessing youths' uptake and retention of and adherence to the HIV Prevention or Treatment Continua. Repeat assessments are conducted every 4 months over 24 months to engage and retain youth and to monitor their status. RESULTS: The project is funded from September 2016 through May 2021. Recruitment began in May 2017 and is expected to be completed by June 2019. We expect to submit the first results for publication by fall 2019. CONCLUSIONS: Using similar, flexible, and adaptable intervention approaches for YLH and YHR, this set of studies may provide a roadmap for communities to broadly address HIV risk among youth. We will evaluate whether the interventions are cost-efficient strategies that can be leveraged to help youth adhere to the actions in the HIV Prevention and Treatment Continua. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/10759.
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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 | 0.056 | 0.035 |
| Meta-epidemiology (narrow) | 0.005 | 0.004 |
| Meta-epidemiology (broad) | 0.005 | 0.008 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.006 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.005 | 0.003 |
| Research integrity | 0.005 | 0.008 |
| Insufficient payload (model declined to judge) | 0.082 | 0.012 |
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".