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Published in: Nutrition Journal 1/2018

Open Access 01-12-2018 | Research

User-documented food consumption data from publicly available apps: an analysis of opportunities and challenges for nutrition research

Authors: Marcus Maringer, Pieter van’t Veer, Naomi Klepacz, Muriel C. D. Verain, Anne Normann, Suzanne Ekman, Lada Timotijevic, Monique M. Raats, Anouk Geelen

Published in: Nutrition Journal | Issue 1/2018

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Abstract

Background

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.

Method

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.

Results

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.

Conclusion

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.
Appendix
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Footnotes
1
iTunes-search module version 1.0.1. Nodejs module to search app data on the iTunes search api. Url: https://​github.​com/​connor/​itunes-node
 
2
Google-play-scraper module version 0.2.1. Nodejs module to search app data on the Google Play store. Url: https://​github.​com/​facundoolano/​google-play-scraper
 
Literature
19.
20.
go back to reference Morrow V, Boddy J, Lamb R. The ethics of secondary data analysis. Novella: NCRM Working Paper; 2014. Morrow V, Boddy J, Lamb R. The ethics of secondary data analysis. Novella: NCRM Working Paper; 2014.
21.
go back to reference van den Puttelaar J, Verain MCD, Onwezen MC, et al. The Potential of Enriching Food Consumption Data by use of Consumer Generated Data: a case from RICHFIELDS, in Measuring Behavior: 10th International Conference on Methods and Techniques in Behavioral Research. Dublin: A. Spink; 2016. van den Puttelaar J, Verain MCD, Onwezen MC, et al. The Potential of Enriching Food Consumption Data by use of Consumer Generated Data: a case from RICHFIELDS, in Measuring Behavior: 10th International Conference on Methods and Techniques in Behavioral Research. Dublin: A. Spink; 2016.
22.
go back to reference Lupton D. Cooking, Eating, Uploading: digital food cultures. In: LeBesco K, Naccarato P, editors. The Handbook of Food and Popular. London Forthcoming: Bloomsbury; 2016. Lupton D. Cooking, Eating, Uploading: digital food cultures. In: LeBesco K, Naccarato P, editors. The Handbook of Food and Popular. London Forthcoming: Bloomsbury; 2016.
23.
go back to reference Hox JJ, Boeije HR. Data Collection, Primary Versus secondary. In: Kempf-Leonard K, editor. Encyclopedia of Social Measurement. San Diego, CA: Academic Press; 2005. Hox JJ, Boeije HR. Data Collection, Primary Versus secondary. In: Kempf-Leonard K, editor. Encyclopedia of Social Measurement. San Diego, CA: Academic Press; 2005.
24.
go back to reference Loshin, D., Knowledge Integrity: Data Ownership, in Data Warehouse magazine (Online) June 8, 2004. 2002. Loshin, D., Knowledge Integrity: Data Ownership, in Data Warehouse magazine (Online) June 8, 2004. 2002.
27.
go back to reference Dufty D, et al. A suggested framework for the quality of big data. In: UNECE big data quality task team; 2014. Dufty D, et al. A suggested framework for the quality of big data. In: UNECE big data quality task team; 2014.
28.
go back to reference Rutishauser IHE, Black AE. Introduction to human nutrition. In: Gibney M, Vorster H, Kok FJ, editors. The Nutrition Society Textbook Series. Oxford: Blackwell Publishing; 2002. p. 225–48. Rutishauser IHE, Black AE. Introduction to human nutrition. In: Gibney M, Vorster H, Kok FJ, editors. The Nutrition Society Textbook Series. Oxford: Blackwell Publishing; 2002. p. 225–48.
30.
go back to reference Adhikari R, Richards D, Scott K. Security and privacy issues related to the use of mobile health apps. in 25th Australasian Conference on Information Systems. 2014; Adhikari R, Richards D, Scott K. Security and privacy issues related to the use of mobile health apps. in 25th Australasian Conference on Information Systems. 2014;
31.
go back to reference Cummings E, Borycki EM, Roehrer E. Issues and considerations for healthcare consumers using mobile applications. Stud Health Technol Inform. 2013;183:227–31.PubMed Cummings E, Borycki EM, Roehrer E. Issues and considerations for healthcare consumers using mobile applications. Stud Health Technol Inform. 2013;183:227–31.PubMed
34.
go back to reference Sharp M, O'Sullivan D. Mobile medical apps and mHealth devices: a framework to build medical apps and mHealth devices in an ethical manner to promote safer use - a literature review. Stud Health Technol Inform. 2017;235:363–7.PubMed Sharp M, O'Sullivan D. Mobile medical apps and mHealth devices: a framework to build medical apps and mHealth devices in an ethical manner to promote safer use - a literature review. Stud Health Technol Inform. 2017;235:363–7.PubMed
49.
go back to reference Research2Guidance. (2016). mHealth App Developer Economics 2016. The current status and trends of the mHealth app market. 6th annual study on mHealth app publishing based on 2,600 plus respondents. Research2Guidance. (2016). mHealth App Developer Economics 2016. The current status and trends of the mHealth app market. 6th annual study on mHealth app publishing based on 2,600 plus respondents.
50.
go back to reference IMS Institute for Healthcare Informatics, Patient Adoption of mHealth. Use, Evidence and Remaining Barriers to Mainstream Acceptance. 2015. IMS Institute for Healthcare Informatics, Patient Adoption of mHealth. Use, Evidence and Remaining Barriers to Mainstream Acceptance. 2015.
53.
go back to reference Choe EK, et al. Understanding quantified-selfers’ practices in collecting and exploring personal data; 2014. p. 1143–52. Choe EK, et al. Understanding quantified-selfers’ practices in collecting and exploring personal data; 2014. p. 1143–52.
54.
go back to reference Li I, Dey A, Forlizzi JA. A stage - based model of personal informatics systems. In: Chi ‘10; 2010. Li I, Dey A, Forlizzi JA. A stage - based model of personal informatics systems. In: Chi ‘10; 2010.
58.
go back to reference European Union, Ethics for researchers: facilitating research excellence in FP7. 2013. European Union, Ethics for researchers: facilitating research excellence in FP7. 2013.
59.
go back to reference European Union. General Data Protection Regulation 2016 9 May 2017]. European Union. General Data Protection Regulation 2016 9 May 2017].
60.
go back to reference Hauck-Lawson A. Introduction to special issue on the food voice. Food, Culture Society. 2004;7(1):24–5.CrossRef Hauck-Lawson A. Introduction to special issue on the food voice. Food, Culture Society. 2004;7(1):24–5.CrossRef
61.
go back to reference Kittler PG, Sucher KP, Nelms MN. Food and culture. 6th ed. Belmont, CA: Wadsworth; 2012. Kittler PG, Sucher KP, Nelms MN. Food and culture. 6th ed. Belmont, CA: Wadsworth; 2012.
63.
go back to reference Maringer M, et al. Food identification by barcode scanning in the Netherlands: a quality assessment of labelled food product databases underlying popular nutrition apps. Public Health Nutrition (in press). 2018. Maringer M, et al. Food identification by barcode scanning in the Netherlands: a quality assessment of labelled food product databases underlying popular nutrition apps. Public Health Nutrition (in press). 2018.
Metadata
Title
User-documented food consumption data from publicly available apps: an analysis of opportunities and challenges for nutrition research
Authors
Marcus Maringer
Pieter van’t Veer
Naomi Klepacz
Muriel C. D. Verain
Anne Normann
Suzanne Ekman
Lada Timotijevic
Monique M. Raats
Anouk Geelen
Publication date
01-12-2018
Publisher
BioMed Central
Published in
Nutrition Journal / Issue 1/2018
Electronic ISSN: 1475-2891
DOI
https://doi.org/10.1186/s12937-018-0366-6

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