Proof-of-concept for integrating multimodal digital health assessments into lifestyle interventions for older adults with dementia risk factors.

Abstract

Multimodal digital health assessments overcome the limitations of patient-reported outcomes by allowing for continuous and passive monitoring but remain underutilized in older adult lifestyle interventions for brain health. Therefore, we aim to (1) report ecological momentary assessment (EMA) and ActiGraph adherence among older adults during a lifestyle intervention; and (2) use dynamic data collected via EMA and ActiGraph to examine person-specific patterns of mindfulness, steps, and sleep throughout the intervention. We analyzed EMA and ActiGraph data from a pilot study of the 8-week My Healthy Brain program (N = 10) lifestyle group for older adults (60+) with subjective cognitive decline. EMA adherence metrics included proportion of EMA completed and the proportion of days with at least 10 mindfulness minutes. ActiGraph GT9X adherence metrics included the number of valid wear days (≥ 7 h) and the number of days participants achieved their step goal. We used linear mixed-effects models to examine person-specific patterns of step count, sleep efficiency, and mindfulness practice. On average, participants completed 39 of the 49 possible EMAs (80%) during the program. ActiGraph adherence was slightly higher than EMA (M = 61.40 days, 87.71%). Participants achieved the daily mindfulness goal (10 min/day) and step goal on 46.32% and 55.10% of days, respectively. Dynamic data revealed that on average, participant step counts increased by approximately 16.5 steps per day (b = 16.495, p = 0.002). However, some participants exhibited no changes while improvements made by other participants returned to baseline levels of activity. There was substantial heterogeneity in trajectories of mindfulness practice and sleep efficiency. EMA and ActiGraph are feasible for older adults enrolled in dementia risk reduction lifestyle interventions. Future studies are needed to better understand how mechanisms of lifestyle behaviors captured by EMA and ActiGraph are related to cognitive outcomes in older adults.