Models of Individual Dietary Behavior Based on Smartphone Data: The Influence of Routine, Physical Activity, Emotion, and Food Environment

• Published in: PloS one Vol. 11; no. 4; p. e0153085
• Main Authors: Seto, Edmund, Hua, Jenna, Wu, Lemuel, Shia, Victor, Eom, Sue, Wang, May, Li, Yan
• Format: Journal Article
• Language: English
• Published: United States Public Library of Science 06.04.2016; Public Library of Science (PLoS)
• Subjects: Accelerometers; Adolescent; Adult; Analysis; Applications programs; Biology and Life Sciences; Cohort Studies; Colleges & universities; Computer engineering; Computer science; Crime prevention; Dairy products; Diet; E-health; Eating behavior; Ecological monitoring; Electrical engineering; Emotions; Energy balance; Engineering and Technology; Engineering schools; Environmental monitoring; Exercise; Experience sampling; Female; Food; Food groups; Global positioning systems; GPS; Health care; Health promotion; Health sciences; Human behavior; Humans; Hypotheses; Male; Maternal & child health; Meals; Medicine and Health Sciences; Mobile Applications; Mobile computing; Modelling; Motor Activity; Nutrition research; Pediatrics; Physical activity; Preventive medicine; Psychology; Public health; Regression analysis; Regression models; Research methodology; Self care (Health); Smart phones; Smartphone; Smartphones; Social Sciences; Studies; Technology application; Time of use; Transplants & implants; Young Adult

Smartphone applications (apps) facilitate the collection of data on multiple aspects of behavior that are useful for characterizing baseline patterns and for monitoring progress in interventions aimed at promoting healthier lifestyles. Individual-based models can be used to examine whether behavior,...