Evaluating the Feasibility and Acceptability of a Digital Pre-Exposure Prophylaxis Navigation and Activation Intervention for Racially and Ethnically Diverse Sexual and Gender Minority Youth (PrEPresent): Protocol for a Pilot Randomized Controlled Trial
Notice bibliographique
Résumé
BACKGROUND: To end the HIV epidemic by 2030, we must double down on efforts to tailor prevention interventions to both young men who have sex with men and transgender and nonbinary youth. There is an urgent need for interventions that specifically focus on pre-exposure prophylaxis (PrEP) uptake in sexual and gender minority youth (SGMY) populations. There are several factors that impact the ability of SGMY to successfully engage in the HIV prevention continuum, including uptake of PrEP. Patient activation, having the knowledge, skills, and self-efficacy to manage one's health, is an important indicator of willingness and ability to manage one's own health and care autonomously. Patient navigation also plays an important role in helping SGMY access PrEP and PrEP care, as navigators help guide patients through the health care system, set up medical appointments, and get financial, legal, and social support. OBJECTIVE: This study aims to evaluate the feasibility and acceptability of a digital PrEP navigation and activation intervention among a racially and ethnically diverse sample of SGMY living in the Los Angeles area. METHODS: In phase 1, we will conduct formative research to inform the development of PrEPresent using qualitative data from key informant interviews involving PrEP care providers and navigators and working groups with SGMY. In phase 2, we will complete 2 rounds of usability testing of PrEPresent with 8-10 SGMY assessing both the intervention content and mobile health delivery platform to ensure features are usable and content is understood. In phase 3, we will conduct a pilot randomized controlled trial to evaluate the feasibility and acceptability of PrEPresent. We will randomize, 1:1, a racially and ethnically diverse sample of 150 SGMY aged 16-26 years living in the Los Angeles area and follow participants for 6 months. RESULTS: Phase 1 (formative work) was completed in April 2021. Usability testing was completed in December 2021. As of June 2023, 148 participants have been enrolled into the PrEPresent pilot randomized controlled trial (phase 3). Enrollment is expected to be completed in July 2023, with final results anticipated in December 2023. CONCLUSIONS: The PrEPresent intervention aims to bridge the gaps in PrEP eligibility and PrEP uptake among racially and ethnically diverse SGMY. By facilitating the delivery of PrEP navigation and focusing on improving patient activation, the PrEPresent intervention has the potential to positively impact the PrEP uptake cascade in the HIV care continuum as well as serve as a model for the tailoring of PrEP interventions based on behavior-based qualifications for PrEP instead of generalized gender-based eligibility. TRIAL REGISTRATION: ClinicalTrials.gov NCT05281393; https://clinicaltrials.gov/ct2/show/NCT05281393. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/50866.
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 | 0,042 | 0,032 |
| Méta-épidémiologie (sens strict) | 0,005 | 0,003 |
| Méta-épidémiologie (sens large) | 0,008 | 0,005 |
| Bibliométrie | 0,003 | 0,003 |
| Études des sciences et des technologies | 0,004 | 0,004 |
| Communication savante | 0,004 | 0,004 |
| Science ouverte | 0,004 | 0,003 |
| Intégrité de la recherche | 0,007 | 0,008 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,058 | 0,008 |
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 ».