Depression deconstructed: Wearables and passive digital phenotyping for analyzing individual symptoms.

ABSTRACT: Wearable technology enables unobtrusive collection of longitudinally dense data, allowing for continuous monitoring of physiology and behavior. These digital phenotypes, or device-based indicators, are frequently leveraged to study depression. However, they are usually considered alongside questionnaire sum-scores which collapse the symptomatic gamut into a general representation of severity. To explore the contributions of passive sensing streams more precisely, associations of nine passive sensing-derived features with self-report responses to Center for Epidemiologic Studies Depression (CES-D) items were modeled. Using data from the NetHealth study on N=469 college students, this work generated mixed ordinal logistic regression models to summarize contributions of pulse, movement, and s

SUBMITTER: Lekkas D 

PROVIDER: S-EPMC10529827 | biostudies-literature | 2023 Sep

REPOSITORIES: biostudies-literature