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Mobility-Based Smartphone Digital Phenotypes for Unobtrusively Capturing Everyday Cognition, Mood, and Community Life-Space in Older Adults: Feasibility, Acceptability, and Preliminary Validity Study

Mobility-Based Smartphone Digital Phenotypes for Unobtrusively Capturing Everyday Cognition, Mood, and Community Life-Space in Older Adults: Feasibility, Acceptability, and Preliminary Validity Study

At study completion, these raw data were extracted from the study server and processed into daily summary features (Table 1) using a publicly available R script developed by Barnett and Onnela [109,110]. GPS data from smartphone devices are prone to large amounts of missing data [111]; therefore, advanced multiple imputation methods based on weighted resampling of the observed data were used to account for missingness before feature calculation.

Katherine Hackett, Shiyun Xu, Moira McKniff, Lido Paglia, Ian Barnett, Tania Giovannetti

JMIR Hum Factors 2024;11:e59974