Mobility-Based Smartphone Digital Phenotypes Unobtrusively Capture Everyday Cognition, Mood, and Community Life-Space in Older Adults: A Pilot Study (Preprint)

Abstract

Current methods of monitoring cognition in older adults are insufficient to address the growing burden of Alzheimer’s disease and related dementias (AD/ADRD). New approaches that are sensitive, scalable, objective, and reflective of meaningful functional outcomes are direly needed. Mobility trajectories and geospatial life space patterns reflect many aspects of cognitive and functional integrity and may be useful proxies of age-related cognitive decline.

We investigated the feasibility, acceptability, and preliminary validity of a 1-month smartphone digital phenotyping protocol to infer everyday cognition, function, and mood in older adults based on passively-obtained GPS data. We also sought to clarify the intrinsic and extrinsic factors that are associated with mobility phenotypes for consideration in future studies.

A total of 37 older adults aged 63-85 with healthy cognition (n=28), Mild Cognitive Impairment (n=5) and mild dementia (n=1) used an open-source smartphone application (mindLAMP) to unobtrusively capture GPS trajectories for 4 weeks. Raw GPS data were processed into interpretable features across categories including activity, inactivity, routine, and location diversity. Monthly average and monthly intraindividual variability (IIV) metrics were calculated for each feature to test a priori hypotheses informed by a neuropsychological model. Comprehensive validation measures collected at baseline were compared alongside monthly GPS features to examine construct validity. Feasibility and acceptability outcomes included participant retention, comprehension of study procedures, technical difficulties, and satisfaction ratings at study debriefing.

All (100%) participants completed the 4-week monitoring period without major adverse events, 100% reported satisfaction with the explanation of study procedures, and 97% reported no feelings of discomfort. Performance on the comprehension of consent quiz was 97% on average and associated with education and race. Technical issues requiring troubleshooting were relatively infrequent, though 41% of participants reported battery drain. Moderate to strong correlations (r>.3) were identified between GPS features and validators. Specifically, individuals with greater mobility activity, less routine, and more location diversity demonstrated better cognition, less functional impairment, less depression, more community participation, and more geospatial life-space on objective and subjective validation measures. Contrary to predictions, greater IIV in mobility was also associated with positive validation outcomes. While many demographic and technology-related factors were not associated with GPS features, income, native English language, season of study participation and occupational status were related.

Theoretically-informed digital phenotypes of mobility are feasibly captured from older adults’ personal smartphone devices and relate to a variety of clinically meaningful measures including cognitive test performance, reported functional decline, mood, and community activity. Future studies should consider the impact of intrinsic and extrinsic factors when interpreting mobility phenotypes. Overall, smartphone digital phenotyping is a promising method to unobtrusively capture relevant risk and resilience factors in the context of aging and AD/ADRD and should continue to be investigated in larger and more diverse samples.