Privacy Perceptions and Concerns in Image-Based Dietary Assessment Systems: Questionnaire-Based Study

Overview

Journal JMIR Hum Factors

Specialty Health Services

Date 2020 Oct 15

PMID 33055060

Citations 1

Authors

Aakash Sharma

Katja P Czerwinska

Lars Brenna

Dag Johansen

Havard D Johansen

Affiliations

Soon will be listed here.

Abstract

Background: Complying with individual privacy perceptions is essential when processing personal information for research. Our specific research area is performance development of elite athletes, wherein nutritional aspects are important. Before adopting new automated tools that capture such data, it is crucial to understand and address the privacy concerns of the research subjects that are to be studied. Privacy as contextual integrity emphasizes understanding contextual sensitivity in an information flow. In this study, we explore privacy perceptions in image-based dietary assessments. This research field lacks empirical evidence on what will be considered as privacy violations when exploring trends in long-running studies. Prior studies have only classified images as either private or public depending on their basic content. An assessment and analysis are thus needed to prevent unwanted consequences of privacy breach and other issues perceived as sensitive when designing systems for dietary assessment by using food images.

Objective: The aim of this study was to investigate common perceptions of computer systems using food images for dietary assessment. The study delves into perceived risks and data-sharing behaviors.

Methods: We investigated the privacy perceptions of 105 individuals by using a web-based survey. We analyzed these perceptions along with perceived risks in sharing dietary information with third parties.

Results: We found that understanding the motive behind the use of data increases its chances of sharing with a social group.

Conclusions: In this study, we highlight various privacy concerns that can be addressed during the design phase. A system design that is compliant with general data protection regulations will increase participants' and stakeholders' trust in an image-based dietary assessment system. Innovative solutions are needed to reduce the intrusiveness of a continuous assessment. Individuals show varying behaviors for sharing metadata, as knowing what the data is being used for, increases the chance of it being shared.

Citing Articles

Up-to-the-Minute Privacy Policies Gossips in Participatory Epidemiological Studies.

Sharma A, Nilsen T, Czerwinska K, Onitiu D, Brenna L, Johansen D Front Big Data. 2021; 4:624424.

PMID: 34056584 PMC: 8155614. DOI: 10.3389/fdata.2021.624424.

References

Wang Y, He Y, Boushey C, Zhu F, Delp E . Context Based Image Analysis With Application in Dietary Assessment and Evaluation. Multimed Tools Appl. 2018; 77(15):19769-19794. PMC: 6127862. DOI: 10.1007/s11042-017-5346-x. View

Boushey C, Kerr D, Wright J, Lutes K, Ebert D, Delp E . Use of technology in children's dietary assessment. Eur J Clin Nutr. 2009; 63 Suppl 1:S50-7. PMC: 2830089. DOI: 10.1038/ejcn.2008.65. View

. Health effects of dietary risks in 195 countries, 1990-2017: a systematic analysis for the Global Burden of Disease Study 2017. Lancet. 2019; 393(10184):1958-1972. PMC: 6899507. DOI: 10.1016/S0140-6736(19)30041-8. View

Pettersen S, Johansen H, Baptista I, Halvorsen P, Johansen D . Quantified Soccer Using Positional Data: A Case Study. Front Physiol. 2018; 9:866. PMC: 6043664. DOI: 10.3389/fphys.2018.00866. View

Zebene Woldaregay A, Henriksen A, Issom D, Pfuhl G, Sato K, Richard A . User Expectations and Willingness to Share Self-Collected Health Data. Stud Health Technol Inform. 2020; 270:894-898. DOI: 10.3233/SHTI200290. View

Lazarte C, Encinas M, Alegre C, Granfeldt Y . Validation of digital photographs, as a tool in 24-h recall, for the improvement of dietary assessment among rural populations in developing countries. Nutr J. 2012; 11:61. PMC: 3547686. DOI: 10.1186/1475-2891-11-61. View

Slegers C, Zion D, Glass D, Kelsall H, Fritschi L, Brown N . Why do people participate in epidemiological research?. J Bioeth Inq. 2015; 12(2):227-37. DOI: 10.1007/s11673-015-9611-2. View

OLoughlin G, Cullen S, McGoldrick A, OConnor S, Blain R, OMalley S . Using a wearable camera to increase the accuracy of dietary analysis. Am J Prev Med. 2013; 44(3):297-301. DOI: 10.1016/j.amepre.2012.11.007. View

Ambrosini G, Hurworth M, Giglia R, Trapp G, Strauss P . Feasibility of a commercial smartphone application for dietary assessment in epidemiological research and comparison with 24-h dietary recalls. Nutr J. 2018; 17(1):5. PMC: 5761106. DOI: 10.1186/s12937-018-0315-4. View

10.

Zeevi D, Korem T, Zmora N, Israeli D, Rothschild D, Weinberger A . Personalized Nutrition by Prediction of Glycemic Responses. Cell. 2015; 163(5):1079-1094. DOI: 10.1016/j.cell.2015.11.001. View

11.

Boushey C, Spoden M, Zhu F, Delp E, Kerr D . New mobile methods for dietary assessment: review of image-assisted and image-based dietary assessment methods. Proc Nutr Soc. 2016; 76(3):283-294. DOI: 10.1017/S0029665116002913. View

12.

Holmlund T, Foltz P, Cohen A, Johansen H, Sigurdsen R, Fugelli P . Moving psychological assessment out of the controlled laboratory setting: Practical challenges. Psychol Assess. 2019; 31(3):292-303. DOI: 10.1037/pas0000647. View

13.

Ashman A, Collins C, Brown L, Rae K, Rollo M . Validation of a Smartphone Image-Based Dietary Assessment Method for Pregnant Women. Nutrients. 2017; 9(1). PMC: 5295117. DOI: 10.3390/nu9010073. View

14.

Allen S, Hopkins W . Age of Peak Competitive Performance of Elite Athletes: A Systematic Review. Sports Med. 2015; 45(10):1431-41. DOI: 10.1007/s40279-015-0354-3. View

15.

Chung C, Agapie E, Schroeder J, Mishra S, Fogarty J, Munson S . When Personal Tracking Becomes Social: Examining the Use of Instagram for Healthy Eating. Proc SIGCHI Conf Hum Factor Comput Syst. 2017; 2017:1674-1687. PMC: 5432132. DOI: 10.1145/3025453.3025747. View

16.

de Vries J, de Groot L, van Staveren W . Dietary assessment in elderly people: experiences gained from studies in the Netherlands. Eur J Clin Nutr. 2009; 63 Suppl 1:S69-74. DOI: 10.1038/ejcn.2008.68. View

17.

Naska A, Lagiou A, Lagiou P . Dietary assessment methods in epidemiological research: current state of the art and future prospects. F1000Res. 2017; 6:926. PMC: 5482335. DOI: 10.12688/f1000research.10703.1. View

18.

Howes E, Boushey C, Kerr D, Tomayko E, Cluskey M . Image-Based Dietary Assessment Ability of Dietetics Students and Interns. Nutrients. 2017; 9(2). PMC: 5331545. DOI: 10.3390/nu9020114. View

19.

Vogt M, Puntschart A, Howald H, Mueller B, Mannhart C, Gfeller-Tuescher L . Effects of dietary fat on muscle substrates, metabolism, and performance in athletes. Med Sci Sports Exerc. 2003; 35(6):952-60. DOI: 10.1249/01.MSS.0000069336.30649.BD. View

20.

Capling L, Beck K, Gifford J, Slater G, Flood V, OConnor H . Validity of Dietary Assessment in Athletes: A Systematic Review. Nutrients. 2017; 9(12). PMC: 5748763. DOI: 10.3390/nu9121313. View