Clinic-Integrated Mobile Health Intervention (“JomPrEP” App) to Improve Uptake of HIV Testing and Pre-exposure Prophylaxis Among Men Who Have Sex With Men in Malaysia: Protocol for an Intervention Development and Multiphase Trial
Bibliographic record
Abstract
BACKGROUND: Men who have sex with men (MSM) are disproportionately affected by the HIV epidemic in Malaysia and globally. Cross-cutting prevention strategies such as mobile health (mHealth), particularly smartphone apps, hold great promise for HIV prevention efforts among Malaysian MSM, especially when linked to HIV testing and pre-exposure prophylaxis (PrEP). OBJECTIVE: This study aims to adapt an existing app to create and test a clinic-integrated app (JomPrEP), a virtual platform to deliver HIV testing and PrEP services for MSM in Malaysia. METHODS: The JomPrEP project involves developing and testing an app-based platform for HIV prevention among Malaysian MSM and will be conducted in 2 phases. In phase I (development phase), we will adapt an existing mHealth app (HealthMindr) to create a new clinic-integrated app called "JomPrEP" to deliver holistic HIV prevention services (eg, HIV testing, PrEP, support services for mental health and substance use) among MSM in Malaysia. During phase II (testing phase), we will use a type I hybrid implementation science trial design to test the efficacy of JomPrEP while gathering information on implementation factors to guide future scale-up in real-world settings. RESULTS: As of September 2022, we have completed phase I of the proposed study. Based on a series of formative work completed during phase I, we developed a fully functional, clinic-integrated JomPrEP app, which provides a virtual platform for MSM in Malaysia to facilitate their engagement in HIV prevention in a fast and convenient manner. Based on participant feedback provided during phase I, we are currently optimizing JomPrEP and the research protocols for a large-scale efficacy trial (phase II), which will commence in January 2023. CONCLUSIONS: Scant HIV prevention resources coupled with entrenched stigma, discrimination, and criminalization of same-sex sexual behavior and substance use hamper access to HIV prevention services in Malaysia. If found efficacious, JomPrEP can be easily adapted for a range of health outcomes and health care delivery services for MSM, including adaptation to other low- and middle-income countries. TRIAL REGISTRATION: ClinicalTrials.gov NCT05325476; https://clinicaltrials.gov/ct2/show/NCT05325476. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/43318.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.014 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".