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Record W2896791420 · doi:10.2196/11502

Connecting Youth and Young Adults to Optimize Antiretroviral Therapy Adherence (YouTHrive): Protocol for a Randomized Controlled Trial

2018· article· en· W2896791420 on OpenAlexvenueno aff
Keith J. Horvath, Richard F. MacLehose, Aldona Martinka, James DeWitt, Lisa Hightow‐Weidman, Patrick S. Sullivan, K. Rivet Amico

Bibliographic record

VenueJMIR Research Protocols · 2018
Typearticle
Languageen
FieldMedicine
TopicHIV/AIDS Research and Interventions
Canadian institutionsnot available
FundersNational Institutes of HealthEunice Kennedy Shriver National Institute of Child Health and Human DevelopmentEmory University
KeywordsRandomized controlled trialIntervention (counseling)MedicineFocus groupYoung adultFamily medicinePsychological interventionPsychologyPhysical therapyGerontologyNursing

Abstract

fetched live from OpenAlex

BACKGROUND: Despite intensive efforts to engage people living with HIV in the United States, less than half of the youth aged 13 to 24 years achieve viral suppression. There is a clear and continued need for innovative behavioral programs that support optimizing adherence among young persons with HIV. OBJECTIVE: There are 3 phases of this project. Phase 1 involves conducting focus groups to obtain feedback from youth about an existing technology-based antiretroviral therapy (ART) adherence intervention. Phase 2 will be used to conduct beta testing with youth to refine and finalize the YouTHrive (YT) intervention. Phase 3 is a randomized controlled trial (RCT) to test the efficacy of the YT intervention among youth living with HIV (YLWH). METHODS: In phase 1, we will conduct 6 focus groups with approximately 8 youths (aged 15-19 years) and young adults (aged 20-24 years), each in 3 US cities to obtain (1) feedback from YLWH about the look and feel and content of an existing adult-focused Web-based ART adherence intervention and (2) suggestions for adapting the intervention for YLWH similar to themselves. Phase 2 will involve updating the existing intervention to include features and functionality recommended by YLWH in phase 1; it will conclude with beta testing with 12 participants to gain feedback on the overall design and ensure proper functionality and ease of navigation. For phase 3, we will enroll 300 YLWH in 6 US cities (Atlanta, Chicago, Houston, New York City, Philadelphia, and Tampa) into a 2-arm prospective RCT. Participants will be randomized 1:1 to YT intervention or control group. The randomization sequence will be stratified by city and use random permuted blocks of sizes 2 and 4. Participants randomized to the control condition will view a weekly email newsletter on topics related to HIV, with the exception of ART adherence, for 5 months. Participants randomized to the YT intervention condition will be given access to the YT site for 5 months. Study assessments will occur at enrollment and 5, 8, and 11 months post enrollment. The primary outcome that will be assessed is sustained viral load (VL), defined as the proportion of participants in each study arm who have suppressed VL at both the 5- and 11-month assessment; the secondary outcome that will be assessed is suppressed VL at both the 5- and 11-month assessment between drug-using and nondrug-using participants assigned to the YT intervention arm. RESULTS: Participant recruitment began in May 2017 for phase 1 of the study. The data collection for aim 3 is anticipated to end in April 2020. CONCLUSIONS: The efficacy trial of the YT intervention will help to fill gaps in understanding the efficacy of mobile interventions to improve ART adherence among at-risk populations. TRIAL REGISTRATION: ClinicalTrials.gov NCT03149757; https://clinicaltrials.gov/ct2/show/NCT03149757 (Archived by WebCite at http://www.webcitation.org/73pw57Cf1). INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/11502.

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 imitation

Not 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.

metaresearch head score (Codex)0.044
metaresearch head score (Gemma)0.038
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.128
Threshold uncertainty score0.427

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0440.038
Meta-epidemiology (narrow)0.0080.004
Meta-epidemiology (broad)0.0130.007
Bibliometrics0.0040.005
Science and technology studies0.0050.004
Scholarly communication0.0060.005
Open science0.0040.003
Research integrity0.0080.012
Insufficient payload (model declined to judge)0.1280.017

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.

Opus teacher head0.190
GPT teacher head0.545
Teacher spread0.354 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designRandomized trial
Domainnot available
GenreProtocol

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".

Quick stats

Citations23
Published2018
Admission routes1
Has abstractyes

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