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Record W7117162586 · doi:10.2196/87601

Evaluation of the Positive Peers Mobile App for Supporting the Viral Suppression of Young People With HIV: Protocol for a Concurrent Mixed Methods Evaluation With Randomized Controlled Clinical Trial and Observational Cohort

2025· article· en· W7117162586 on OpenAlexvenueno aff
Mary M. Step, L. Anthony Catania, Jennifer McMillen Smith, Steven L. Lewis, Yanis Bitar, Vinay K. Cheruvu, Kristen Andrea Berg, Jeffrey S. Hallam, Ann Avery

Bibliographic record

VenueJMIR Research Protocols · 2025
Typearticle
Languageen
FieldHealth Professions
TopicMobile Health and mHealth Applications
Canadian institutionsnot available
Fundersnot available
KeywordsObservational studyRandomized controlled trialProtocol (science)Clinical trialCohortCohort studyViral loadPopulation

Abstract

fetched live from OpenAlex

BACKGROUND: People at greatest risk for poor HIV outcomes include young (13-34) people of color who have sex with men. Individuals in this population are least likely to be aware of their HIV status and are at the highest risk for disengaging from medical care and antiretroviral therapy. The Positive Peers mobile app (PPA) was designed to engage this population with real-time social support, HIV and healthy lifestyle information, and medical management tools. We expect that greater PPA engagement will predict key HIV care outcomes. Study predictions are grounded in a user-centric model of digital media use and the perceived affordances of the PPA. OBJECTIVE: This study aims to determine the optimal deployment of the PPA in clinical settings (at enrollment vs delayed start) and to compare intervention outcomes with a no-intervention, observation-only condition. The PPA is designed specifically for key HIV disparity populations, including younger sexual, gender, racial, and ethnic minorities. METHODS: The Positive Peers Intervention Trial (PoPIT) is a multisite, randomized clinical trial designed to evaluate the effectiveness of the PPA as a tool for use in clinical settings. Trial arms compare the immediate deployment of the PPA with usual care and observation only. This protocol outlines a mixed methods design consisting of concurrent prospective self-report questionnaires, in-depth interviews with PPA users, and medical record review. PoPIT questionnaires include measures of social determinants of health, HIV-related stigma, perceptions of digital media use, self-efficacy, substance use, and social support. Multiple aspects of PPA intervention engagement are measured natively within the app. Outcomes include HIV National Quality Forum indicators and perceived HIV-related stigma. RESULTS: The research protocol (1R01MD019185-01) was funded for US $903,363.00 in direct costs by the National Institute for Minority Health and Health Disparities on September 24, 2023, for 5 years. The study began recruiting patients on June 3, 2024, and will continue accrual until November 27, 2026. CONCLUSIONS: Findings will provide evidence of the usefulness of the PPA as a support tool in HIV clinical care. Primary results will inform optimization of PPA deployment and evaluate a theoretical model of user engagement with a mobile health management app. Qualitative data will provide a phenomenological description of intervention engagement and perceived user efficacy. TRIAL REGISTRATION: ClinicalTrials.gov NCT06388109; https://clinicaltrials.gov/ct2/show/NCT06388109. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/87601.

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)0.084
metaresearch head score (Gemma)0.065
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 score0.084
Threshold uncertainty score0.445

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0840.065
Meta-epidemiology (narrow)0.0080.004
Meta-epidemiology (broad)0.0100.008
Bibliometrics0.0040.005
Science and technology studies0.0060.005
Scholarly communication0.0080.005
Open science0.0050.004
Research integrity0.0080.010
Insufficient payload (model declined to judge)0.0760.018

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 head0.427
GPT teacher head0.718
Teacher spread0.290 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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