Optimizing an mHealth Intervention to Improve Uptake and Adherence to HIV Pre-exposure Prophylaxis in Young Transgender Women: Protocol for a Multi-Phase Trial
Notice bibliographique
Résumé
BACKGROUND: Vulnerable adolescents and emerging adults (aged 18-29 years), particularly young transgender women, are among the fastest-growing HIV positive populations worldwide. Thailand has the highest adult HIV seroprevalence in Asia, with a rate of infection among this population of 18%. Widespread technology offers opportunities for innovative mobile health (mHealth) interventions. Pre-exposure prophylaxis (PrEP) is an efficacious HIV prevention strategy recommended for at-risk individuals. PrEP is highly effective when taken as prescribed, but uptake and adherence have been low, with high discontinuation rates among youth. OBJECTIVE: We propose to develop and pilot a multi-component, technology-based intervention to promote PrEP usage. We will adapt an existing 2-session, technology-delivered, motivational interviewing-based intervention to focus on PrEP use in transgender women in Thailand. We call this the Motivational Enhancement System for PrEP Uptake and Adherence (MES-PrEP). We will also refine and enhance YaCool, a mobile app with integrated text messaging developed and used clinically by our Thai team. The new version of the app is called Enhanced YaCool, and it enables self-management of gender and sexual health (including PrEP). Our primary aim is to develop and assess the preliminary efficacy of this mHealth intervention. METHODS: We will utilize a multiphase optimization strategy (MOST) to identify the most effective intervention component or combination of components to improve PrEP usage in Thai transgender women. The study includes two phases: phase I (R21) includes qualitative interviews with key stakeholders to explore barriers and facilitators of PrEP usage through thematic analysis to inform intervention adaptation. Following this, we will adapt and beta-test MES-PrEP and Enhanced YaCool for functionality and feasibility using a community advisory board of HIV-negative Thai transgender women. In phase II (R33), we will conduct a MOST design-based trial to evaluate the feasibility, acceptability, and preliminary efficacy of MES-PrEP and Enhanced YaCool. Eighty HIV-negative participants who are currently taking PrEP and 80 participants who are not will be randomized to four conditions: (1) standard PrEP counseling (the control condition); (2) MES-PrEP and standard PrEP counseling; (3) Enhanced YaCool and standard PrEP counseling; and (4) MES-PrEP, Enhanced YaCool, and standard PrEP counseling. Feasibility and acceptability of the intervention will be assessed through usage patterns and the System Usability Scale. Preliminary impact will be assessed by evaluating the proportion of participants who initiate PrEP and their level of adherence to PrEP. Assessments will be at baseline and 1, 3, 6, 9, and 12 months postintervention. Biomarkers of adherence to PrEP, HIV, and other sexually transmitted infections will be collected. RESULTS: Upon project completion, we will have an optimized mHealth intervention to support the use of PrEP by transgender women that will be ready for testing in a larger efficacy trial. CONCLUSIONS: Even though transgender women in Thailand face increasing risks of HIV, few interventions have targeted them. Effective developmentally and culturally tailored interventions are needed to prevent HIV transmission in this high-risk population. TRIAL REGISTRATION: ClinicalTrials.gov NCT05262426; https://clinicaltrials.gov/ct2/show/NCT05262426. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/37659.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,020 | 0,020 |
| Méta-épidémiologie (sens strict) | 0,005 | 0,003 |
| Méta-épidémiologie (sens large) | 0,009 | 0,006 |
| Bibliométrie | 0,002 | 0,002 |
| Études des sciences et des technologies | 0,004 | 0,003 |
| Communication savante | 0,003 | 0,003 |
| Science ouverte | 0,004 | 0,003 |
| Intégrité de la recherche | 0,006 | 0,009 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,064 | 0,010 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».