(PS12-58) A Data-driven Approach to Optimize Digital Health Intervention Reach Rates for Older Adults

Background: Older adults face barriers to the uptake of digital health interventions (DHIs), such as low awareness, usability challenges, and low perceived usefulness. Yet evidence supports the efficacy of DHIs in this population, including for eating regulation. We designed a DHI that targets binge eating for adults of any age with recurrent binge eating. Given the unique barriers older adults face to DHI uptake, we sought to learn how well we engage older adults in research on our DHI. Our findings will inform opportunities to optimize DHI research participation in this subpopulation.

Methods: We analyzed recruitment data from a pilot clinical trial evaluating a 16-week DHI for binge eating. Participants were recruited via flyers, research participation websites (e.g., ResearchMatch), and online platforms (e.g., social media, Craigslist). Descriptives were calculated at each phase of enrollment—screening (online survey), baseline assessment (interview and questionnaires), and study enrollment—and at intervention completion, and were compared to national 12-month prevalence estimates of binge eating disorder (BED; 1% prevalence among U.S. adults, with 17% of that subset aged 60+). Rates of conversion between enrollment phases also were compared between older (60+) and younger (18-59) adults presenting for the trial. As an additional comparative analysis, we assessed screening data from a co-design study comprised of interviews to design the DHI, which used similar recruitment strategies but may have had differential appeal from the clinical trial.

Results: In the clinical trial, older adults comprised 9% of people who completed screening, which was nearly half the national estimated proportion of older adults with BED. However, 16% of the 81 participants who were eligible for and enrolled in the trial were aged 60+, indicating that older adults were more likely to progress through phases of trial enrollment. Specifically, older adults were more likely than younger adults to be eligible after screening (40% vs. 29%), to complete the baseline assessment (62% vs. 55%), and to be eligible for the trial following baseline (50% vs. 39%). Yet 23% of enrolled older adults discontinued the intervention, a higher proportion of dropout than enrolled younger adults (8%). In the co-design study, 11% of screens were from older adults, which also was below national estimates.

Discussion: Older adults were underrepresented at screening in both studies, suggesting our recruitment pathways may be inappropriate or insufficient to reach them. Even so, older adults were more likely to be eligible for and enroll in the trial, potentially indicating that after presenting to the trial, they had a firmer commitment to joining. Yet their elevated discontinuation rates suggest opportunities to improve DHI engagement in this population. Despite our small sample, this exploratory analysis highlights that further research is needed to learn how to improve recruitment reach and inclusiveness prior to screening through targeted recruitment strategies. We also must improve our understanding of older adults’ needs and thus DHI requirements. Human-centered design methods that engage older adults could help improve digital health equity in this population.