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Erschienen in:
Unsupervised Learning of Robust Representations for Change Detection on Sentinel-2 Earth Observation Images Kapitel lesen Erstes Kapitel lesen

2020 | OriginalPaper | Buchkapitel

Dietary Intake Assessment: From Traditional Paper-Pencil Questionnaires to Technology-Based Tools

verfasst von : Elske M. Brouwer-Brolsma, Desiree Lucassen, Marielle G. de Rijk, Anne Slotegraaf, Corine Perenboom, Karin Borgonjen, Els Siebelink, Edith J. M. Feskens, Jeanne H. M. de Vries

Erschienen in: Environmental Software Systems. Data Science in Action

Verlag: Springer International Publishing

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Abstract

Self-reported methods of recall and real-time recording are the most commonly used approaches to assess dietary intake, both in research as well as the health-care setting. The traditional versions of these methods are limited by various methodological factors and burdensome for interviewees and researchers. Technology-based dietary assessment tools have the potential to improve the accuracy of the data and reduce interviewee and researcher burden. Consequently, various research groups around the globe started to explore the use of technology-based tools. This paper provides an overview of the: (1) most-commonly used and generally accepted methods to assess dietary intake; (2) errors encountered using these methods; and (3) web-based and app-based tools (i.e., Compl-eatTM, Traqq, Dutch FFQ-TOOLTM, and “Eetscore”) that have been developed by researchers of the Division of Human Nutrition and Health of Wageningen University during the past years.

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Vorheriges Kapitel Unsupervised Learning of Robust Representations for Change Detection on Sentinel-2 Earth Observation Images
Nächstes Kapitel Computational Infrastructure of SoilGrids 2.0
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Metadaten
Titel
Dietary Intake Assessment: From Traditional Paper-Pencil Questionnaires to Technology-Based Tools
verfasst von
Elske M. Brouwer-Brolsma
Desiree Lucassen
Marielle G. de Rijk
Anne Slotegraaf
Corine Perenboom
Karin Borgonjen
Els Siebelink
Edith J. M. Feskens
Jeanne H. M. de Vries
Copyright-Jahr
2020
Buch
Environmental Software Systems. Data Science in Action

Print ISBN: 978-3-030-39814-9

Electronic ISBN: 978-3-030-39815-6

Copyright-Jahr: 2020

DOI
https://doi.org/10.1007/978-3-030-39815-6_2

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