Accepted for/Published in: JMIR mHealth and uHealth
Date Submitted: Apr 24, 2020
Date Accepted: Mar 8, 2021
Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.
Electronic Health Intervention Based on the HIV Risk Prediction tool for HIV Prevention Among Men Who Have Sex with Men in China: A Randomized Controlled Trial
ABSTRACT
Background:
Electronic health (E-health) intervention based on risk stratification has not been applied to HIV behavioral intervention among MSM.
Objective:
The study aimed to evaluate the efficacy of targeted behavioral interventions based on the HIV infection risk prediction tool in promoting HIV testing and reducing high-risk behavior among MSM in China.
Methods:
An online randomized, controlled clinical trial was conducted using the WeChat mobile social media for 12 weeks. MSM were randomly assigned to the intervention or control group. In the intervention group, a comprehensive intervention package was distributed through WeChat, while the control group received only information regarding HIV/AIDS transmission and prevention. At baseline and 12-week follow-up, data on HIV-related risk behavior and HIV testing behavior were evaluated.
Results:
192 MSM were recruited and assigned to the intervention group (N=96) or control group (N=96). At week 12, the total cohort retention rate was 87.5%. The number of male sexual partners in the past 3 months (P3M) in the intervention group was significantly lower than that reported in the control group (3.51±4.1 vs. 6.01±11.4, mean difference: −2.5; 95% CI: −5.115–0.115; P=0.045); the rate of condom use with casual sexual partners was higher than that recorded in the control group (86.8% vs. 70.1%, OR=2.805; 95% CI: 1.230–6.393; P=0.012); The rate of intension to test for HIV in the following 30 days in the intervention group was marginally higher than that observed in the control group (89.9% vs.80.2%, OR=2.198; 95% CI: 0.902–5.352; P=0.069). The incremental cost-effectiveness ratio of the E-health intervention was 131.60 USD on reducing one sexual partner and 19.70 USD on increment of one percent condom usage with casual partners.
Conclusions:
Comprehensive intervention strategies based on the HIV infection risk prediction tool can reduce the number of male sexual partners of MSM, and increase the rate of condom use with casual partners. Hence, this is a very promising preventive intervention strategy for MSM, especially in high HIV epidemic areas. Clinical Trial: www.chictr.org.cn, ChiCTR1800017268,registered date: 2018/7/20
Citation
