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Low medication adherence when initiating antiretroviral treatment (ART) is a key barrier to HIV virologic suppression, resulting in avoidable cases of drug resistance, death, and viral transmission. Routinized pill-taking can lead to successful long-term ART adherence, and short-term behavioral economics-based supports are a novel way to overcome the limited success of existing routinization interventions. This study proposes to test this combined approach for promoting long-term ART adherence using a Stage III Sequential, Multiple Assignment, Randomized Trial (SMART) design in one of the largest HIV clinics in Uganda to identify the most cost-effective adaptive intervention that if found effective is generalizable to other settings and other chronic diseases.
Full description
Building on a previous R34 study, the investigators will adapt and deliver the INMIND approach to 550 ART initiators at Mildmay. Participants will initially be randomized to receive either usual care (Control, n=275) or daily text messages (Messages, n=275) to support adherence routines. At months 1 and 2, participants may revise their adherence plans. Those showing <80% adherence in month 3 will be re-randomized to receive either monthly or monthly escalated prize incentives for the next three months. Adherence will be monitored for an additional 12 months (total follow-up: 18 months) to assess long-term routine maintenance and recovery after interruptions. The SMART design will help identify the most cost-effective intervention sequencing. A cost-effectiveness analysis and stakeholder dissemination will support future scale-up. The investigators hypothesize that Messages will be more effective than Control as a first-stage treatment; that monthly escalated prizes will be more effective than monthly prizes as a second-stage treatment; and that the mechanisms of lack of Salience and Present Bias will mediate the effect of INMIND on our primary and secondary outcomes.
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550 participants in 4 patient groups
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Yvonne Karamagi Site Principal Investigator; Lillian Lukuse
Data sourced from clinicaltrials.gov
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