Network Analysis of Ecological Momentary Assessment Data for Monitoring and Understanding Eating Behavior

Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingAcademicpeer-review

2 Citations (Scopus)

Abstract

Ecological momentary assessment (ema) techniques have been blooming during the last years due to the emergence of smart devices (like pdas and smartphones) that allow the collection of repeated assessments of several measures (predictors) that affect a target variable. Eating behavior studies can benefit from ema techniques by analysing almost real-time information regarding food intake and the related conditions and circumstances. In this paper, an ema method protocol to study eating behavior is presented along with the mobile application developed for this purpose. Mixed effects and vector autoregression are utilized for conducting a network analysis of the data collected and lead to inferring knowledge for the connectivity between different conditions and their effect on eating behavior.
Original languageEnglish
Title of host publicationSmart Health: International Conference, ICSH 2015, Phoenix, AZ, USA, November 17-18, 2015. Revised Selected Papers
EditorsXiaolong Zheng, Dajun Daniel Zeng, Hsinchun Chen, J. Scott Leischow
Place of PublicationCham
PublisherSpringer
Pages43-54
Number of pages12
ISBN (Print)978-3-319-29175-8
DOIs
Publication statusPublished - 2016

Cite this

Spanakis, G., Weiss, G., Boh, B., & Roefs, A. (2016). Network Analysis of Ecological Momentary Assessment Data for Monitoring and Understanding Eating Behavior. In X. Zheng, D. D. Zeng, H. Chen, & J. S. Leischow (Eds.), Smart Health: International Conference, ICSH 2015, Phoenix, AZ, USA, November 17-18, 2015. Revised Selected Papers (pp. 43-54). Springer. https://doi.org/10.1007/978-3-319-29175-8_5