Cited by 231Mobile Health and mHealth ApplicationsNutrition, Health and Food BehaviorNutritional Studies and Diet

Use of technology in children’s dietary assessment

Open access
Boushey, C J, Kerr, D A, Wright, J, Lutes, K D, Ebert, D S, Delp, E J·2009·European Journal of Clinical Nutrition

Abstract

Background Information on dietary intake provides some of the most valuable insights for mounting intervention programmes for the prevention of chronic diseases. With the growing concern about adolescent overweight, the need to accurately measure diet becomes imperative. Assessment among adolescents is problematic as this group has irregular eating patterns and they have less enthusiasm for recording food intake.Subjects/methods We used qualitative and quantitative techniques among adolescents to assess their preferences for dietary assessment methods.Results Dietary assessment methods using technology, for example, a personal digital assistant (PDA) or a disposable camera, were preferred over the pen and paper food record.Conclusions There was a strong preference for using methods that incorporate technology such as capturing images of food. This suggests that for adolescents, dietary methods that incorporate technology may improve cooperation and accuracy. Current computing technology includes higher resolution images, improved memory capacity and faster processors that allow small mobile devices to process information not previously possible. Our goal is to develop, implement and evaluate a mobile device (for example, PDA, mobile phone) food record that will translate to an accurate account of daily food and nutrient intake among adolescents. This mobile computing device will include digital images, a nutrient database and image analysis for identification and quantification of food consumption. Mobile computing devices provide a unique vehicle for collecting dietary information that reduces the burden on record keepers. Images of food can be marked with a variety of input methods that link the item for image processing and analysis to estimate the amount of food. Images before and after the foods are eaten can estimate the amount of food consumed. The initial stages and potential of this project will be described.

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1038/ejcn.2008.65

Cites

18 of 18 references verified0 citation errors · 0 not checkable

Statistics

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Cites

Flagged first, then by citations

Research works printed but not linked: 1

  1. Burke G The digital classroom: handhelds are dramatically rewriting approaches to 3 R’s Lafayette Journal and Courier 2005 B5

Cited by

Sorted by citations

Authors
Boushey, C. J., Kerr, D. A., Wright, J., Lutes, K. D., Ebert, D. S., & Delp, E. J.
Affiliations
  • Purdue University West Lafayette (US)
  • Curtin University (AU)
Corresponding author
Boushey, C J
Venue
European Journal of Clinical Nutrition
Published
2009-02
Volume
63
Issue
S1
Pages
S50-S57
ISSN
  • 0954-3007 (ISSN-L)
  • 1476-5640
OpenAlex
W2121825214
Cited by
231
References
18
Citations by year
2026: 4 · 2025: 5 · 2024: 3 · 2023: 4 · 2022: 4 · 2021: 4 · 2020: 10 · 2019: 11 · 2018: 16 · 2017: 29 · 2016: 14 · 2015: 24 · 2014: 17 · 2013: 17 · 2012: 29
FWCI
41.04
Type
journal article
Language
en
Open access
Locations
  • European Journal of Clinical Nutrition (publishedVersion)
  • PubMed (publishedVersion)
  • Europe PMC (PubMed Central) (acceptedVersion)
  • PubMed Central (acceptedVersion)
  • eSpace (Curtin University) (submittedVersion)
Funders
  • National Cancer Institute (U01CA130784)
  • National Institute of Diabetes and Digestive and Kidney Diseases (R01DK073711)
Topics
  • Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
  • Health Sciences › Nursing › Nutrition and Dietetics › Nutrition, Health and Food Behavior
  • Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Nutritional Studies and Diet
Keywords
dietary assessment, adolescents, mobile devices, personal digital assistants, food photography, image analysis, food intake recording, adolescent overweight
MeSH terms
Adolescent, Child, Data Collection, Diet, Diet Surveys, Female, Humans, Male, Photography, Pilot Projects, Surveys and Questionnaires, Technology, Diet Records, Computer Peripherals, Focus Groups, Asian People

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review