Presentation (CTI)

OBJECTIVES: Digital health technologies are increasingly integrated in rare disease research for decentralized data collection (Mao et al., 2025). However, work outside this disease space suggests digital health research often inadequately represents patient demographic diversity, including underrepresenting older adults and overrepresenting urban-located and privately insured individuals (Curtis, et al., 2022; Pratap et al., 2020). We investigated whether these limitations extend to digital health research on rare and chronic conditions.
METHODS: As of June 2026, 1,659 participants had enrolled in seven rare and chronic condition-specific prospective, observational studies via the Folia Health (FH) app. Upon enrollment, participants self-reported demographic data, including age, race, ethnicity, gender, geographical region, education, and healthcare coverage. Participants then provided granular, patient-reported longitudinal data on the day-to-day experience of their condition.
RESULTS: Analysis revealed a robust distribution across ages, with 12.5% of participants being 60 years or older. Additionally, participants came from a wide range of geographical regions (Suburban area: 40.0%; Small city: 21.0%; Rural: 19.0%); educational backgrounds (Bachelor’s degree: 33.3%; High school diploma: 29.2%; Master’s degree: 15.3%); and health care coverage (Private health insurance: 48.5%; Medicaid: 20.4%; Medicare: 10.7%). As is typical in health research, a larger proportion identified as female (66.0%), white (75.0%) and non-Hispanic/Latino (87.3%); however, there was still representation of other racial groups (Asian: 4.2%; Black/African American: 8.6%; More than one race: 5.9%).
CONCLUSIONS: FH is engaging a large, diverse group of participants across multiple demographics. Compared with established limitations, the current work especially excelled in engaging older adults and individuals outside urban areas without private health insurance. This adds to the growing digital health technology literature, specifically indicating that it can assist in understanding the burden and unmet clinical needs of rare and chronic conditions.