An Interactive Voice Response Software to Improve the Quality of Life of People Living With HIV in Uganda: Randomized Controlled Trial

International audience ; Background Following the successful scale-up of antiretroviral therapy (ART), the focus is now on ensuring good quality of life (QoL) and sustained viral suppression in people living with HIV. The access to mobile technology in the most burdened countries is increasing rapidly, and therefore, mobile health (mHealth) technologies could be leveraged to improve QoL in people living with HIV. However, data on the impact of mHealth tools on the QoL in people living with HIV are limited to the evaluation of SMS text messaging; these are infeasible in high-illiteracy settings. Objective The primary and secondary outcomes were to determine the impact of interactive voice response (IVR) technology on Medical Outcomes Study HIV QoL scores and viral suppression at 12 months, respectively. Methods Within the Call for Life study, ART-experienced and ART-naïve people living with HIV commencing ART were randomized (1:1 ratio) to the control (no IVR support) or intervention arm (daily adherence and pre-appointment reminders, health information tips, and option to report symptoms). The software evaluated was Call for Life Uganda, an IVR technology that is based on the Mobile Technology for Community Health open-source software. Eligibility criteria for participation included access to a phone, fluency in local languages, and provision of consent. The differences in differences (DIDs) were computed, adjusting for baseline HIV RNA and CD4. Results Overall, 600 participants (413 female, 68.8%) were enrolled and followed-up for 12 months. In the intervention arm of 300 participants, 298 (99.3%) opted for IVR and 2 (0.7%) chose SMS text messaging as the mode of receiving reminders and health tips. At 12 months, there was no overall difference in the QoL between the intervention and control arms (DID=0.0; P=.99) or HIV RNA (DID=0.01; P=.94). At 12 months, 124 of the 256 (48.4%) active participants had picked up at least 50% of the calls. In the active intervention participants, high users (received >75% of ...