Integrating a Combination HIV Prevention Intervention Into a Widely Used Geosocial App for Chinese Men Who Have Sex With Men: Protocol for a Single-Arm Pilot and Repeated Cross-Sectional Study
Notice bibliographique
Résumé
BACKGROUND: HIV disproportionately affects men who have sex with men in China. However, HIV prevention services use among this population remains limited, in part due to concerns of privacy and sexual identity disclosure. These concerns might be addressed through telehealth services. OBJECTIVE: This study was designed to assess the feasibility and acceptability of Blued+, which integrates an HIV prevention services package into a geosocial networking app commonly used by Chinese men who have sex with men. METHODS: The study design was a single-arm pilot of the Blued+ intervention among men who have sex with men, using repeated cross-sectional surveys of an external population for comparison. For the pilot study, men were recruited from Beijing and Chengdu. A 3-month standard-of-care period with measurement at enrollment and month 0 (baseline) was followed by a 12-month intervention period with measurement at months 3, 6, 9, and 12. During the intervention period, participants received the enhanced version of the Blued app (Blued+) with HIV testing, linkage to care as needed, choice of condoms and condom-compatible lubricants, and pre-exposure prophylaxis (PrEP) services. PrEP was provided through in-app counseling and prescription, followed by lab tests at local clinics and mailed medication. Three cross-sectional surveys in months 0, 6, and 12 were administered to men in Beijing and Chengdu who were not enrolled in another HIV prevention study. These participants had access to the standard Blued geosocial networking app and local health services. The primary outcome of feasibility was the uptake of home HIV testing and PrEP. The coprimary outcome of intervention acceptability was measured with the System Usability Scale. RESULTS: The run-in period was launched on July 15, 2022, with recruitment completed on August 24, 2022. The baseline period concluded in November 2022, and all follow-up assessments were completed by December 2023. At baseline, the pilot study enrolled 423 participants, and the cross-sectional comparison enrolled 1314 participants. Participants in the pilot were young (mean age 30, SD 7 years) and educated (324/423, 76.6% reported a college degree or higher), and most (302/423, 71.4%) reported HIV testing in the prior 3 months. Most participants (404/423, 95.5%) had heard of PrEP, and over a quarter had used PrEP (114/423, 27%). Participants in the comparison population had comparable sociodemographic characteristics, reporting HIV testing (501/857, 58.5%) in the prior 3 months, PrEP awareness (723/857, 84.4%), and PrEP use in the last 3 months (182/857, 15.4%). CONCLUSIONS: This pilot study will provide preliminary evidence regarding the feasibility and acceptability of the Blued+ intervention. The study findings will provide evidence setting the foundation for future research that involves embedding prevention platforms into apps that are already widely used. If preliminary impact is observed, future research would include a hybrid effectiveness implementation trial of the intervention. TRIAL REGISTRATION: ClinicalTrials.gov NCT06647173; https://clinicaltrials.gov/study/NCT06647173. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/69536.
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 | 0,013 | 0,008 |
| Méta-épidémiologie (sens strict) | 0,004 | 0,003 |
| Méta-épidémiologie (sens large) | 0,005 | 0,003 |
| Bibliométrie | 0,002 | 0,001 |
| Études des sciences et des technologies | 0,005 | 0,002 |
| Communication savante | 0,002 | 0,002 |
| Science ouverte | 0,003 | 0,003 |
| Intégrité de la recherche | 0,004 | 0,005 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,027 | 0,004 |
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 ».