4. Discussion
PREDHiCT
The current remote decentralized trial utilized a mixed-methods approach to develop a mobile application that provided novel education, navigation, and access experiences about clinical trials to a sample of 98 participants who have a personal or family history of a cardiometabolic condition. One of the primary innovative features of the intervention’s mobile application, PREDHiCT, is that it uses an artificial intelligence bot to curate a vast amount of content daily from the internet to provide personalized and tailored educational materials to participants about clinical trials and a variety of health conditions. A second unique feature of PREDHiCT is its intimate navigation of participants throughout the clinical trial journey. PREDHiCT weaves traditional health behavior tracking (sleep and physical activity), general health education about health conditions they care about, and call-to-action opportunities to combat health conditions the participant cares about—a strategy that engenders altruistic feelings about and willingness to participate in a trial. Ultimately, participating in a clinical trial is linked to health promotion behavior. Doing so highlights a third unique feature of PREDHiCT, which is making clinical trial information and opportunities more accessible to participants. Our findings indicate that these three unique features increased altruism and clinical trial literacy, but not willingness to participate in a trial. 