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
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.013 | 0.008 |
| Meta-epidemiology (narrow) | 0.004 | 0.003 |
| Meta-epidemiology (broad) | 0.005 | 0.003 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.027 | 0.004 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".