Optimizing participation in digital health studies: understanding appointment attendance.

Abstract

This study examined whether attendance at online digital health research appointments in the American Women Assessing Risk Epidemiologically (AWARE) study was associated with (1) participant age, (2) scheduling factors (time of day, day of week, month), (3) appointment confirmation, and (4) HIV behavioral risk factors. We analyzed scheduling and eligibility screening data from AWARE, a 24-month U.S.-based longitudinal digital cohort of cisgender women at elevated likelihood of HIV seroconversion. Participant demographic and behavioral data were merged with the study team's Outlook calendar. Chi-square tests and logistic regression models assessed associations between appointment attendance and participant characteristics and scheduling factors. Women aged ≥50 years had higher odds of missing baseline visits compared to those aged 20-29 years (44.7% vs 32.3%). Appointments scheduled at 2:00 pm (45.7%), 4:00 pm (45.2%), and 8:00 am (40.2%) had higher no-show rates than other times. No-show rates were lowest on Fridays (30.2%) and during March (27.7%) and June (25.2%). Confirming appointments 24 hours in advance significantly reduced no-shows compared to no confirmation (19.0% vs 51.6%). Histories of having been physically hurt (44.2% vs 32.1%), forced to have sexual activities (41.8% vs 34.1%) and incarcerated (39.3% vs 33.4%) were also associated with higher no-show rates. Similar patterns were observed for rescheduled visits. Attendance in digital research was influenced by age, scheduling, and structural vulnerabilities. Incorporating digital access support into study design and grant budgets may reduce disparities, improve retention, and enhance efficiency.