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Article details
Title
User-documented food consumption data from publicly available apps: an analysis of opportunities and challenges for nutrition research
Published in
Nutrition Journal, June 2018
DOI 10.1186/s12937-018-0366-6
Pubmed ID
Authors
Abstract

The need for a better understanding of food consumption behaviour within its behavioural context has sparked the interest of nutrition researchers for user-documented food consumption data collected outside the research context using publicly available nutrition apps. The study aims to characterize the scientific, technical, legal and ethical features of this data in order to identify the opportunities and challenges associated with using this data for nutrition research. A search for apps collecting food consumption data was conducted in October 2016 against UK Google Play and iTunes storefronts. 176 apps were selected based on user ratings and English language support. Publicly available information from the app stores and app-related websites was investigated and relevant data extracted and summarized. Our focus was on characteristics related to scientific relevance, data management and legal and ethical governance of user-documented food consumption data. Food diaries are the most common form of data collection, allowing for multiple inputs including generic food items, packaged products, or images. Standards and procedures for compiling food databases used for estimating energy and nutrient intakes remain largely undisclosed. Food consumption data is interlinked with various types of contextual data related to behavioural motivation, physical activity, health, and fitness. While exchange of data between apps is common practise, the majority of apps lack technical documentation regarding data export. There is a similar lack of documentation regarding the implemented terms of use and privacy policies. While users are usually the owners of their data, vendors are granted irrevocable and royalty free licenses to commercially exploit the data. Due to its magnitude, diversity, and interconnectedness, user-documented food consumption data offers promising opportunities for a better understanding of habitual food consumption behaviour and its determinants. Non-standardized or non-documented food data compilation procedures, data exchange protocols and formats, terms of use and privacy statements, however, limit possibilities to integrate, process and share user-documented food consumption data. An ongoing research effort is required, to keep pace with the technical advancements of food consumption apps, their evolving data networks and the legal and ethical regulations related to protecting app users and their personal data.

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Mendeley demographics

Mendeley demographics

The data shown below were compiled from readership statistics for 153 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Geographical breakdown
Country Count As %
Unknown 153 100%

Demographic breakdown

Readers by professional status
Readers by professional status Count As %
Student > Master 26 17%
Researcher 16 10%
Student > Bachelor 14 9%
Student > Doctoral Student 13 8%
Student > Ph. D. Student 13 8%
Other 26 17%
Unknown 45 29%
Readers by discipline
Readers by discipline Count As %
Medicine and Dentistry 18 12%
Computer Science 14 9%
Nursing and Health Professions 11 7%
Social Sciences 11 7%
Psychology 9 6%
Other 40 26%
Unknown 50 33%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 10 July 2020.
All research outputs
#24,114,619
of 26,851,865 outputs
Outputs from Nutrition Journal
#1,508
of 1,593 outputs
Outputs of similar age
#304,339
of 345,116 outputs
Outputs of similar age from Nutrition Journal
#19
of 19 outputs
Altmetric has tracked 26,851,865 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,593 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 41.0. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
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We're also able to compare this research output to 19 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.