Literature DB >> 24976425

Feasibility and validity of mobile phones to assess dietary intake.

Darren B Sharp1, Margaret Allman-Farinelli2.   

Abstract

Current limitations of conventional dietary assessment methods restrict the establishment of diet-disease relationships and efficacy of dietary interventions. Technology, in particular the use of mobile phones, may help resolve methodologic limitations, in turn improving the validity of dietary assessment and research and associated findings. This review aims to evaluate the validity, feasibility, and acceptability of dietary assessment methods that have been deployed on mobile phone platforms. In August 2013, electronic databases for health sciences were searched for English, peer-reviewed, full-text articles, published from January 1, 2001 onward; and accompanied by a hand search of available relevant publications from universities and government bodies. Studies were not limited by design, length, setting, or population group. Of 194 articles, 12 met eligibility criteria: mobile phone as the dietary recording platform and validation of energy and/or macronutrient intake against another dietary or biological reference method. Four dietary recoding methods had been validated on mobile phone platforms: electronic food diary, food photograph-assisted self-administered, 24 h recall, food photograph analysis by trained dietitians, and automated food photograph analysis. All mobile phone dietary assessment methods showed similar, but not superior, validity or reliability when compared with conventional methods. Participants' satisfaction and preferences for mobile phone dietary assessment methods were higher than those for conventional methods, indicating the need for further research. Validity testing in larger and more diverse populations, over longer durations is required to evaluate the efficacy of these methods in dietary research.
Copyright © 2014 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Dietary assessment; Food diary; Food photograph; Reliability; Smartphone

Mesh:

Year:  2014        PMID: 24976425     DOI: 10.1016/j.nut.2014.02.020

Source DB:  PubMed          Journal:  Nutrition        ISSN: 0899-9007            Impact factor:   4.008


  56 in total

1.  Validity of a Digital Diet Estimation Method for Use with Preschool Children.

Authors:  Theresa Nicklas; Noemi G Islam; Rabab Saab; Rebecca Schulin; Yan Liu; Nancy F Butte; John W Apolzan; Candice A Myers; Corby K Martin
Journal:  J Acad Nutr Diet       Date:  2017-06-19       Impact factor: 4.910

Review 2.  Emerging trends of technology-based dietary assessment: a perspective study.

Authors:  Xueyin Zhao; Xiaochen Xu; Xiuyan Li; Xi He; Yang Yang; Shankuan Zhu
Journal:  Eur J Clin Nutr       Date:  2020-10-20       Impact factor: 4.016

Review 3.  Technology Interventions to Manage Food Intake: Where Are We Now?

Authors:  Margaret Allman-Farinelli; Luke Gemming
Journal:  Curr Diab Rep       Date:  2017-09-23       Impact factor: 4.810

Review 4.  A Digital Ecosystem of Diabetes Data and Technology: Services, Systems, and Tools Enabled by Wearables, Sensors, and Apps.

Authors:  Nathaniel D Heintzman
Journal:  J Diabetes Sci Technol       Date:  2015-12-20

5.  Beyond Nutrient Intake: Use of Digital Food Photography Methodology to Examine Family Dinnertime.

Authors:  Morgan L McCloskey; Susan L Johnson; Traci A Bekelman; Corby K Martin; Laura L Bellows
Journal:  J Nutr Educ Behav       Date:  2019-02-28       Impact factor: 3.045

6.  Computer vision-based carbohydrate estimation for type 1 patients with diabetes using smartphones.

Authors:  Marios Anthimopoulos; Joachim Dehais; Sergey Shevchik; Botwey H Ransford; David Duke; Peter Diem; Stavroula Mougiakakou
Journal:  J Diabetes Sci Technol       Date:  2015-04-16

Review 7.  Technology-based interventions for weight management: current randomized controlled trial evidence and future directions.

Authors:  Andrea T Kozak; Joanna Buscemi; Misty A W Hawkins; Monica L Wang; Jessica Y Breland; Kathryn M Ross; Anupama Kommu
Journal:  J Behav Med       Date:  2016-10-25

8.  Development and Validation of an Objective, Passive Dietary Assessment Method for Estimating Food and Nutrient Intake in Households in Low- and Middle-Income Countries: A Study Protocol.

Authors:  Modou L Jobarteh; Megan A McCrory; Benny Lo; Mingui Sun; Edward Sazonov; Alex K Anderson; Wenyan Jia; Kathryn Maitland; Jianing Qiu; Matilda Steiner-Asiedu; Janine A Higgins; Tom Baranowski; Peter Olupot-Olupot; Gary Frost
Journal:  Curr Dev Nutr       Date:  2020-02-07

9.  Smartphone Applications for Promoting Healthy Diet and Nutrition: A Literature Review.

Authors:  Steven S Coughlin; Mary Whitehead; Joyce Q Sheats; Jeff Mastromonico; Dale Hardy; Selina A Smith
Journal:  Jacobs J Food Nutr       Date:  2015

10.  'Boden Food Plate': Novel Interactive Web-based Method for the Assessment of Dietary Intake.

Authors:  Alice Meroni; Nyssa Jualim; Nicholas Fuller
Journal:  J Vis Exp       Date:  2018-09-18       Impact factor: 1.355

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