Sociodemographic characteristics of missing data in digital phenotyping

• Published in: Scientific reports Vol. 11; no. 1; pp. 15408 - 11
• Main Authors: Kiang, Mathew V., Chen, Jarvis T., Krieger, Nancy, Buckee, Caroline O., Alexander, Monica J., Baker, Justin T., Buckner, Randy L., Coombs, Garth, Rich-Edwards, Janet W., Carlson, Kenzie W., Onnela, Jukka-Pekka
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 29.07.2021; Nature Publishing Group; Nature Portfolio
• Subjects: 692/308/174; 692/700/478; Accelerometry - methods; Adolescent; Adult; Bayes Theorem; Bayesian analysis; Black People; Child; Cognition; Data collection; Data Collection - methods; Education; Environment; Feasibility Studies; Female; Follow-Up Studies; Geographic Information Systems; Global positioning systems; GPS; Humanities and Social Sciences; Humans; Male; Mathematical models; Middle Aged; Missing data; multidisciplinary; Natural environment; Nervous system; Phenotyping; Science; Science (multidisciplinary); Sensitivity analysis; Sensors; Smartphone - instrumentation; Smartphones; Social Behavior; Sociodemographics; Sociological Factors; Young Adult

The ubiquity of smartphones, with their increasingly sophisticated array of sensors, presents an unprecedented opportunity for researchers to collect longitudinal, diverse, temporally-dense data about human behavior while minimizing participant burden. Researchers increasingly make use of smartphone...