Efficacy and Impact of Digital HIV Care Navigation in Young People Living With HIV in San Francisco, California: Prospective Study

Abstract

Background Young people are disproportionately impacted by HIV infection and exhibit poor HIV care continuum outcomes. Mobile health (mHealth) interventions are promising approaches to meet the unique needs of young people living with HIV. Youth-focused interventions are needed to improve HIV care continuum outcomes. Objective This study assessed the preliminary efficacy and impact of a digital HIV care navigation intervention among young people living with HIV in San Francisco. Health electronic navigation (eNavigation or eNav) is a 6-month, text message–based, digital HIV care navigation intervention, in which young people living with HIV are connected to their own HIV care navigator through text messaging to improve engagement in HIV primary care. Methods This study had a single-arm, prospective, pre-post design. The analysis included 120 young men who have sex with men or transwomen living with HIV aged between 18 and 34 years. We analyzed self-reported sociobehavioral information pre- and postintervention at baseline and 6 months, which was collected using computer-assisted self-interviewing surveys. We characterized the sample and built generalized estimating equation (GEE) models to assess differences in HIV care continuum outcomes at baseline and 6 months. Results The characteristics according to the intervention completion status were not different from those of the overall sample. The mean age of the participants was 27.75 years (SD 4.07). Most participants (103/120, 85.8%) identified as men, and the sample was racially/ethnically diverse. At baseline, majority (99/120, 82.5%) of the participants had recently received primary HIV care, yet this was more likely in those who completed the intervention than in those who did not (54/60, 90% vs 45/60, 75%; χ21=4.68, P=.03). More than half of the sample reported taking antiretroviral therapy (92/120, 76.7%) and having an undetectable viral load (65/120, 54.2%). The 6-month follow-up surveys were completed by 73.3% (88/120) of participants, and these participants were not characteristically different from the overall sample at baseline. GEE models indicated that participants had increased odds of viral suppression at 6 months as compared with baseline. No relevant additive or multiplicative interactions were noted on comparing outcome effects over time according to intervention completion. Conclusions Digital HIV care navigation fills a critical gap in public health and HIV care systems, making these systems more responsive and accountable to the needs of the most vulnerable individuals. Our intervention bridges the time between primary care visits with interactive, tailored, personalized, and peer-delivered social support; information; and motivational interviewing to scaffold behavioral change. This study is part of the next wave of system-informed mHealth intervention research that will offer potentially disruptive solutions to traditional in-person delivered interventions and improve the health of the most vulnerable individuals. International Registered Report Identifier (IRRID) RR2-10.2196/16406

Results from a peer-based digital systems navigation intervention to increase HIV prevention and care behaviors of young trans women in Rio de Janeiro, Brazil

“…16 We adapted an evidence-based peer and mHealth delivered systems navigation intervention for implementation digitally using social media and text messaging to interact with participants.. 17 Our approach was designed in response to the enormous challenges young trans women face in accessing HIV prevention and care in Brazil and leverages prior successes with mHealth to engage young trans women in research and interventions. 18,19 This analysis describes the results of our pilot BeT intervention to improve engagement of Brazilian young trans women in HIV prevention and HIV care.…”

Need for Inclusive Consideration of Transgender and Gender Diverse People in E-Health Services: A Systematic Review

“…Among the 17 quantitative studies included, there were 4 RCTs [42,43,63,70] and 13 nonrandomized studies (including 4 comparative studies [65,68,69,72], 8 non-comparative single-arm studies [14,15,[58][59][60][61]67,73], and 1 non-interventional study [30]). Across the five domains of RoB 2, the selected RCT studies were convincing.…”

“…This was true for the US MOTIVES [70,71], evaluated in a quasi-experimental randomized pilot study of 218 service users (largely MSM sample, including 30.2% and 36.7% trans women in the intervention groups with mean ages of 34.8 and 35.2 years, respectively), the Indonesian RUMAH SELA [72] non-randomized study project with 168 participants (largely MSM and drug user sample, of which 29.17% were trans women with a mean age of 25.6 years), and the US TGD-specific non-randomized usability study project Trans Women Connected [45] with 16 trans women and non-binary individuals (mean age 34.5 years). Two US studies focused on increasing the utilization of HIV-related health care, namely, weCare [39] (process evaluation with 32 participants, average age 25.2 years and including 27.78% trans women), and an unnamed eNavigation [73] addressed to 120 participants (largely MSM sample, including 14.17% trans women with an average age of 27.75 years).…”

“…For the videoconferencing services, service users had to have access to an internet-enabled device with a microphone and camera (e.g., laptop). While another 6 studies [39,45,[70][71][72][73] dealt with mobile health apps, as mentioned above, for the remaining 10 included studies [38,46,58,59,61,[63][64][65][66][67], web-accessible computers were in the foreground due to concepts such as games, educational programs, or forums.…”

“…E-health services explicitly for TGD people consistently resulted in positive evaluations [30,[43][44][45][46]. The same is true for e-health studies with combined community samples (i.e., LGBTQIA+ samples and mixed samples in the case of course formats designed to be open to all user groups) [38,39,[62][63][64][65][66][67][69][70][71][72][73]. However, these studies provided only limited information on satisfaction and evaluation of the e-health content with regard to its suitability as TGD specific.…”