Recruitment of Youth Living With HIV to Optimize Adherence and Virologic Suppression: Testing the Design of Technology-Based Community Health Nursing to Improve Antiretroviral Therapy (ART) Clinical Trials
Bibliographic record
Abstract
BACKGROUND: Despite advances in HIV diagnosis and treatment, adolescents and young adults 12-25 years old have high HIV incidence, poor engagement and retention in treatment, and low rates of adherence and virologic suppression when compared to their older counterparts. HIV has emerged as a chronic disease for which antiretroviral therapy (ART) adherence is critical for virologic suppression and long-term survival. Virologic suppression has been elusive for many youth with HIV (YHIV). Novel strategies designed to facilitate health care systems' support for YHIV between medical visits are essential for improving ART adherence, virologic suppression, and long-term survival. OBJECTIVE: The aim of this study is to compare the effectiveness of a technology-enhanced community health nursing intervention (TECH2CHECK) to a standard of care (SOC) control group for improving ART adherence and subsequent viral suppression using a randomized trial design. The objectives are to assess the feasibility, acceptability, and cost-effectiveness of TECH2CHECK as compared to SOC for management of HIV in the outpatient setting and to examine the sustainability of self-care behavior, adherence, and virologic suppression among youth following the intervention period. METHODS: We will recruit 120 adherence-challenged YHIV being followed at clinics specializing in HIV care in the Baltimore-Washington metropolitan area and in Jacksonville. Eligible participants complete an audio, computer-assisted self-interview and are randomized to either TECH2CHECK intervention or the SOC (60 participants in each arm). The primary outcome of interest is virologic suppression (viral load <20 copies/mL) and improved treatment adherence. Participants in the intervention arm receive community health nursing visits at 2 weeks, 6 weeks, 10 weeks, 14 weeks, and 26 weeks. The intervention arm also receives SMS messaging comprising daily adherence and appointment reminders and positive reinforcement for medication adherence daily for 2 weeks, on alternate days for 2 weeks, thrice weekly for 1 month, weekly for 3 months, and every 2 weeks for the rest of the study duration. The control group receives appointment reminders and SOC per clinic protocol. Exploratory analysis will be conducted to determine differences in medication adherence and virologic suppression in the 2 arms and to assess cost-effectiveness and study feasibility and acceptability. RESULTS: In the first 23 months of the study (July 2018-April 2020), 56 (55%) of 102 eligible patients were enrolled and randomized. At present, participating youths are primarily African American (53/56, 95%), male (37/56, 66%), and ≥18 years old (53/56, 95%). Follow-up study visits, as required per the protocol, have been completed by 77% (43/56), 94% (45/48), 95% (37/39), 96% (24/25), and 100% (10/10) of participants at the 1-month, 3-month, 6-month, 12-month, and 18-month follow-ups, respectively. CONCLUSIONS: Preliminary accrual and retention data suggest that TECH2CHECK is feasible and acceptable. TRIAL REGISTRATION: ClinicalTrials.gov NCT03600103 https://clinicaltrials.gov/ct2/show/NCT03600103. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/23480.
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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 | 0.064 | 0.070 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| 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".