Developing and Implementing Provider-Training and Evidence-Based Tools to Support Pre-exposure Prophylaxis (PrEP) Decision-Making and Increase PrEP Adherence Among Young Men Who Have Sex With Men: Protocol for the PrEP Choice Longitudinal Cohort Study
Notice bibliographique
Résumé
BACKGROUND: Despite the availability of highly effective HIV pre-exposure prophylaxis (PrEP), uptake and adherence to PrEP among young men who have sex with men (YMSM) remains low, limiting its impact on the prevention of HIV infection. Strategies that incorporate an array of prevention options and provide YMSM and their providers with tailored education and support tools, including tools to support shared decision-making, are needed. OBJECTIVE: The goals of the Centers for Disease Control and Prevention (CDC)-funded PrEP Choice study include the development and deployment of CDC guideline-consistent PrEP provider training and the implementation of evidence-based provider- and client-facing PrEP education and support tools. Under this initiative, the CDC funded 2 research projects, Florida State University (the Expanding PrEP in Communities of Color [EPICC] project), and Columbia University (the mChoice project). METHODS: Providers from both projects will complete the PrEP Choice online training, which was developed to educate providers on PrEP options and how to engage clients in open discussions around sexual health and PrEP options. EPICC project providers will also attend online tailored motivational interviewing (TMI) training sessions, and mChoice project providers will view a training video on cultural competency and humility in PrEP care. Following training, each project will enroll a cohort of 400 participants receiving care from study providers and follow them for 12-18 months. Participants will complete online surveys every 3 months and provide biomarkers to assess PrEP adherence. Electronic health record (EHR) data will be collected every 6 months to provide additional information on clinic attendance, PrEP prescriptions, and HIV/sexually transmitted infection (STI) testing. Each project will provide cohort participants with a unique digital health tool to support the PrEP choice and ongoing adherence. The study will assess the effectiveness of training and educational and support tools in practice and the critical factors associated with the successful uptake of and adherence to PrEP by participants. The study will also monitor patterns of PrEP use among YMSM, including types of PrEP and switching between types. RESULTS: Formative work to develop and prepare the tools for implementation was completed in 2023. The EPICC project began provider training in early 2024, and the mChoice project began in spring 2024. Cohort enrollment for both projects began after provider training began. CONCLUSIONS: Given the changing PrEP landscape, implementation of provider education and tools to maximize uptake and adherence is needed. By delivering culturally competent and interactive provider training on PrEP options, the study will help providers counsel and guide participants on the effective and safe use of PrEP. The digital health tools created will support participant adherence to help them optimize PrEP benefits. Through the cohort design, the PrEP Choice study will provide real-world data about PrEP use that will be critical for informing future guidelines and tools. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/64186.
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 | 0,051 | 0,031 |
| Méta-épidémiologie (sens strict) | 0,003 | 0,003 |
| Méta-épidémiologie (sens large) | 0,003 | 0,004 |
| Bibliométrie | 0,003 | 0,003 |
| Études des sciences et des technologies | 0,006 | 0,003 |
| Communication savante | 0,003 | 0,003 |
| Science ouverte | 0,004 | 0,004 |
| Intégrité de la recherche | 0,004 | 0,008 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,054 | 0,012 |
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 ».