Frailty in older adults is a multidimensional syndrome characterized by reduced physiological resilience and heightened vulnerability to adverse outcomes, yet conventional assessments remain largely clinic-based. This study evaluated the feasibility and explanatory utility of smartphone-based digital lifelogs for assessing frailty in community-dwelling older adults. In a prospective observational study, 300 participants (mean age 73.30, SD 5.37 years) from three sites in Seoul, South Korea, used a custom mobile application for two weeks that passively collected sensor-derived gait speed, 30 s sit-to-stand counts, and daily and hourly step counts, alongside self-reported ratings of perceived exertion and subjective health. Frailty Index (FI) scores were computed, and Pearson correlations, hierarchical linear regression, and independent linear regression were applied to examine associations and model explanatory performance. Significant correlations were observed between FI and gait speed, sit-to-stand performance, daily step counts, perceived exertion, and subjective health. Incorporating digital lifelogs significantly improved explained variance in frailty beyond clinical indicators (ΔR2 = 0.183), with gait speed and daily step counts emerging as key predictors. A model including only digital lifelogs also significantly associated with frailty (R2 = 0.288). These findings suggest that smartphone-based lifelogging offers a feasible, practical, and informative method for two-week monitoring and cross-sectional assessment in community settings.
Keywords: digital health; digital lifelogs; frailty; mobile health; older adults.