Men who have sex with men (MSM) account for nearly two-thirds all of new HIV infections in the United States (US) and young MSM (YMSM) are the only risk group experiencing a significant increase in HIV incidence. Among youth, 67 percent report not disclosing to their first time sex partners. Disclosing of one’s HIV status is important for accessing support which can lead to improved medication adherence and retention in care. Those who disclose are more likely to use condoms with uninfected sex partners and mathematical modeling estimates that increased HIV status disclosure to sex partners may reduce transmissions by 40-60%. Further, disclosure may motivate uninfected sex partners to seek testing and reduce their own HIV transmission behaviors.
Given the potential benefits and challenges associated with disclosure, there is a need for sophisticated interventions that can assist MSM, with the disclosure process. Virtual reality provides a unique environment for users to practice HIV disclosure. Artificial intelligence (AI) driven disclosure may offer advantages over in-person role play through the use of realistic avatars that represent potential romantic partners, and probabilistic settings where users envision having disclosure conversations. Users have the opportunity to practice disclosing and experience a variety of responses and outcomes.
During Phase I of this project we developed an iPad based virtual reality system that features three avatars, two virtual locations and three disclosure scenarios which represent a variety of common disclosure experiences and contexts experienced by YMSM (aged 16-29 years). In Phase II we will further enhance Tough Talks™ and develop a full-feature automated version to test via a multi-site, randomized controlled trial (RCT) through the newly created Center for Innovative Technologies (iTech) across the Prevention and Care Continuum, an NIH-funded center to support adolescent HIV research.
The aims of this Phase II SBIR are 1) Refine and enhance the current Tough Talks™ disclosure scenarios to include additional content, characters and virtual environments. Formative work with YMSM will inform development and we will work with a leader in AI software to incorporate natural language into the AI driven scenarios; 2) Develop the Tough Talks™ stand-alone intervention. This fully automated intervention will include the AI driven disclosure scenarios created in aim 1 as well as a virtual disclosure coach to guide participants through the intervention goal-setting interactive exercises and interactive educational videos. Following development, a technical pilot to optimize functionality and technical performance will be conducted with 8-10 YMSM and; 3) Conduct a three-arm combined efficacy/effectiveness trial to compare the intervention delivered online (Arm 1) versus in the clinic (Arm 2) compared to standard of care (SOC) disclosure messaging only. Primary outcomes of HIV viral load and condomless anal intercourse (CAI) will be assessed at intervention completion (1 month) and at 6-month follow-up. Modeling will estimate transmissions averted and costs of each arm. (Months 19-36)
Investigator: Sara Legrand
Partners: Joe Egger, Alyssa Platt, UNC