Author(s):
- Pamela McKinney
- Andrew Martin Cox
- Laura Sbaffi
Abstract:
Background: The tracking, or logging, of food intake and physical activity is increasing among people, and as a result there is increasing evidence of a link to improvement in health and well-being. Crucial to the effective and safe use of logging is a user’s information literacy.
Objective: The aim of this study was to analyze food and activity tracking from an information literacy perspective.
Methods: An online survey was distributed to three communities via parkrun, diabetes.co.uk and the Irritable Bowel Syndrome Network.
Results: The data showed that there were clear differences in the logging practices of the members of the three different communities, as well as differences in motivations for tracking and the extent of sharing of said tracked data. Respondents showed a good understanding of the importance of information accuracy and were confident in their ability to understand tracked data, however, there were differences in the extent to which food and activity data were shared and also a lack of understanding of the potential reuse and sharing of data by third parties.
Conclusions: Information literacy in this context involves developing awareness of the issues of accurate information recording, and how tracked information can be applied to support specific health goals. Developing awareness of how and when to share data, as well as of data ownership and privacy, are also important aspects of information literacy.
Documentation:
References:
- Lupton D. The Quantified Self. Cambridge: Polity Press; 2016.
- Lupton D. Health promotion in the digital era: a critical commentary. Health Promot Int 2015 Mar;30(1):174-183. [CrossRef] [Medline]
- Dennison L, Morrison L, Conway G, Yardley L. Opportunities and challenges for smartphone applications in supporting health behavior change: qualitative study. J Med Internet Res 2013;15(4):1-12 [FREE Full text] [CrossRef] [Medline]
- Dute D, Bemelmans W, Breda J. Using mobile apps to promote a healthy lifestyle among adolescents and students: A review of the theoretical basis and lessons learned. JMIR mHealth uHealth 2016;4(2):e39. [Medline]
- Mintel. Mintel Reports. 2018. Mobile phones-UK-April 2018 URL: http://reports.mintel.com/display/859075/?__cc=1
- Mintel. Mintel Academic. 2017. Mobile device apps-UK-November 2017 URL: http://academic.mintel.com/display/793809/
- Klasnja P, Pratt W. Healthcare in the pocket: mapping the space of mobile-phone health interventions. J Biomed Inform 2012 Feb;45(1):184-198 [FREE Full text] [CrossRef] [Medline]
- Schoeppe S, Alley S, Van Lippevelde W, Bray NA, Williams SL, Duncan MJ, et al. Efficacy of interventions that use apps to improve diet, physical activity and sedentary behaviour: a systematic review. Int J Behav Nutr Phys Act 2016 Dec 07;13:127 [FREE Full text] [CrossRef] [Medline]
- Epstein D, Lee N, Kang J, Agapie E, Schroeder J, Pina L, et al. Examining Menstrual Tracking to Inform the Design of Personal Informatics Tools. In: Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems. 2017 Presented at: CHI Conference on Human Factors in Computing Systems; May 06 – 11, 2017; Denver, Colorado p. 6876-6888 URL: http://dl.acm.org/citation.cfm?doid=3025453.3025635
- Schroeder J, Chung C, Epstein D, Karkar R, Parsons A, Murinova N, et al. Examining Self-Tracking by People with Migraine. In: DIS ’18 Proceedings of the 2018 Designing Interactive Systems Conference. 2018 Presented at: DIS 18: Designing Interactive Systems Conference; June 09 – 13, 2018; Hong Kong- China p. 135-148 URL: https://dl.acm.org/citation.cfm?id=3196738 [CrossRef]
- Wang Q, Egelandsdal B, Amdam GV, Almli VL, Oostindjer M. Diet and Physical Activity Apps: Perceived Effectiveness by App Users. JMIR Mhealth Uhealth 2016;4(2):e33 [FREE Full text] [CrossRef] [Medline]
- Rapp A, Tirabeni L. Personal Informatics for Sport. ACM Trans Comput-Hum Interact 2018 Jun 28;25(3):1-30. [CrossRef]
- Ancker JS, Witteman HO, Hafeez B, Provencher T, Van de Graaf M, Wei E. “You Get Reminded You’re a Sick Person”: Personal Data Tracking and Patients With Multiple Chronic Conditions. J Med Internet Res 2015;17(8):e202 [FREE Full text] [CrossRef] [Medline]
- Mentis H, Komlodi A, Schrader K, Phipps M, Gruber-Baldini A, Yarbrough K, et al. Crafting a View of Self-Tracking Data in the Clinical Visit. In: CHI ’17 Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems. 2017 Presented at: 2017 CHI Conference on Human Factors in Computing Systems; May 06 – 11, 2017; Denver, Colorado p. 5800-5812 URL: https://dl.acm.org/citation.cfm?id=3025589 [CrossRef]
- Lunde P, Nilsson B, Bergland A, Kværner KJ, Bye A. The Effectiveness of Smartphone Apps for Lifestyle Improvement in Noncommunicable Diseases: Systematic Review and Meta-Analyses. J Med Internet Res 2018 May 04;20(5):e162-e112 [FREE Full text] [CrossRef] [Medline]
- Chen J, Lieffers J, Bauman A, Hanning R, Allman-Farinelli M. The use of smartphone health apps and other mobile health (mHealth) technologies in dietetic practice: a three country study. J Hum Nutr Diet 2017 Aug;30(4):439-452. [CrossRef] [Medline]
- Flores Mateo G, Granado-Font E, Ferré-Grau C, Montaña-Carreras X. Mobile Phone Apps to Promote Weight Loss and Increase Physical Activity: A Systematic Review and Meta-Analysis. J Med Internet Res 2015;17(11):e253 [FREE Full text] [CrossRef] [Medline]
- Mintel. Mintel Reports. 2017. Wearable technology-UK-December 2017 URL: http://reports.mintel.com/display/794377/
- Bert F, Giacometti M, Gualano M, Siliquini R. Smartphones and health promotion: A review of the evidence. J Med Syst 2014;38(1):9995. [CrossRef]
- Chartered Institute of Library and Information Professionals. CILIP. 2018. CILIP definition of Information Literacy 2018 URL: https://infolit.org.uk/ILdefinitionCILIP2018.pdf
- Papen U. Conceptualising information literacy as social practice: a study of pregnant women’s information practices. Inf Res 2013;18(2):1 [FREE Full text]
- Lloyd A. Informing practice: information experiences of ambulance officers in training and on‐road practice. Journal of Documentation 2009 Apr 24;65(3):396-419. [CrossRef] [Medline]
- Marshall A, Henwood F, Carlin L, Guy E, Sinozic T, Smith H. Information to fight the flab: findings from the Net.Weight Study. JIL 2009 Dec 08;3(2):39-52. [CrossRef]
- Lloyd A, Bonner A, Dawson-Rose C. The health information practices of people living with chronic health conditions: Implications for health literacy. Journal of Librarianship and Information Science 2013 May 17;46(3):207-216. [CrossRef]
- Cox A, McKinney P, Goodale P. Food logging: an information literacy perspective. Aslib Journal of Info Mgmt 2017 Mar 20;69(2):184-200. [CrossRef]
- Yates C. Exploring variation in the ways of experiencing health information literacy: A phenomenographic study. Library & Information Science Research 2015 Jul;37(3):220-227. [CrossRef]
- Yates C, Partridge H, Bruce C. Learning wellness: how ageing Australians experience health information literacy. The Australian Library Journal 2009 Aug;58(3):269-285. [CrossRef]
- Sharon T. Self-Tracking for Health and the Quantified Self: Re-Articulating Autonomy, Solidarity, and Authenticity in an Age of Personalized Healthcare. Philos. Technol 2016 Apr 18;30(1):93-121. [CrossRef]
- Paige S, Stellefson M, Krieger J, Anderson-Lewis C, Cheong J, Stopka C. Proposing a Transactional Model of eHealth Literacy: Concept Analysis. J Med Internet Res 2018;20(10):e10175. [Medline]
- Yates C, Stoodley I, Partridge H, Bruce C, Cooper H, Day G, et al. Exploring Health Information Use by Older Australians within Everyday Life. Library Trends 2012;60(3):460-478. [CrossRef]
- Ernsting C, Dombrowski SU, Oedekoven M, Kanzler M, Kuhlmey A, Gellert P. Using Smartphones and Health Apps to Change and Manage Health Behaviors: A Population-Based Survey. J Med Internet Res 2017 Apr 05;19(4):e101 [FREE Full text] [CrossRef] [Medline]
- Rusin M, Arsand E, Hartvigsen G. Functionalities and input methods for recording food intake: a systematic review. Int J Med Inform 2013 Aug;82(8):653-664. [CrossRef] [Medline]
- Sharp DB, Allman-Farinelli M. Feasibility and validity of mobile phones to assess dietary intake. Nutrition 2014;30(11-12):1257-1266. [CrossRef] [Medline]
- St. Jean B, Jindal G, Chan K. “You Have to Know Your Body!”: The Role of the Body in Influencing the Information Behaviors of People with Type 2 Diabetes. Library Trends 2018;66(3):289-314. [CrossRef]
- Rooksby J, Rost M, Morrison A, Chalmers M. Personal tracking as lived informatics. In: CHI ’14 Proceedings of the SIGCHI Conference on Human Factors in Computing Systems. 2014 Presented at: SIGCHI Conference on Human Factors in Computing Systems; April 26 – May 01, 2014; Toronto, Canada p. 1163-1172 URL: https://dl.acm.org/citation.cfm?id=2557039 [CrossRef]
- Paré G, Leaver C, Bourget C. Diffusion of the Digital Health Self-Tracking Movement in Canada: Results of a National Survey. J Med Internet Res 2018 May 02;20(5):e177 [FREE Full text] [CrossRef] [Medline]
- Azar KMJ, Lesser LI, Laing BY, Stephens J, Aurora MS, Burke LE, et al. Mobile applications for weight management: theory-based content analysis. Am J Prev Med 2013 Nov;45(5):583-589. [CrossRef] [Medline]
- Krebs P, Duncan DT. Health App Use Among US Mobile Phone Owners: A National Survey. JMIR Mhealth Uhealth 2015;3(4):e101 [FREE Full text] [CrossRef] [Medline]
- Rapp A, Cena F. Personal informatics for everyday life: How users without prior self-tracking experience engage with personal data. International Journal of Human-Computer Studies 2016 Oct;94:1-17. [CrossRef]
- Hoy MB. Personal Activity Trackers and the Quantified Self. Med Ref Serv Q 2016;35(1):94-100. [CrossRef] [Medline]
- Yang R, Shin E, Newman M, Ackerman M. When fitness trackers don’t ‘fit’: end-user difficulties in the assessment of personal tracking device accuracy. In: Proceedings of the 2015 ACM International Joint Conference on Pervasive and Ubiquitous Computing. 2015 Presented at: the 2015 ACM International Joint Conference on Pervasive and Ubiquitous Computing; September 07 – 11, 2015; Osaka, Japan p. 623-634 URL: https://dl.acm.org/citation.cfm?id=2804269 [CrossRef]
- Vitak J, Liao Y, Kumar P, Zimmer M, Kritikos K. Privacy attitudes and data valuation among fitness tracker users. In: Transforming Digital Worlds: 13th International Conference, iConference 2018. Sheffield: Springer International Publishing; 2018 Presented at: Transforming Digital Worlds: 13th International Conference, iConference 2018; March 25-28, 2018; Sheffield p. 229-239. [CrossRef]
- Ackerman L. Mobile health and fitness applications and information privacy: report to California Consumer Protection Foundation. San Diego, California: Privacy Rights Clearinghouse; 2013. URL: https://www.privacyrights.org/mobile-medical-apps-privacy-consumer-report.pdf
- The Guardian. 2018 Mar 30. Hackers steal data of 150 million MyFitnessPal app users URL: https://www.theguardian.com/technology/2018/mar/30/hackers-steal-data-150m-myfitnesspal-app-users-under-armour
- Ba S, Wang L. Digital health communities: The effect of their motivation mechanisms. Decision Support Systems 2013 Nov;55(4):941-947. [CrossRef]
- American Gastroenterological Association. American Gastroenterological Association medical position statement: Irritable Bowel Syndrome. Gastroenterology 2002 Nov;123(6):2105-2107. [CrossRef]
- National Health Service. 2017. What is IBS? Irritable Bowel Syndrome (IBS) URL: https://www.nhs.uk/conditions/irritable-bowel-syndrome-ibs/ [accessed 2018-08-02]
- Burke LE, Wang J, Sevick MA. Self-monitoring in weight loss: a systematic review of the literature. J Am Diet Assoc 2011 Jan;111(1):92-102 [FREE Full text] [CrossRef] [Medline]
- Shim J, Oh K, Kim H. Dietary assessment methods in epidemiologic studies. Epidemiol Health 2014;36:e2014009. [Medline]
- James P, Weissman J, Wolf J, Mumford K, Contant C, Hwang W, et al. Comparing GPS, Log, Survey, and Accelerometry to Measure Physical Activity. Am J Health Behav 2016;40(1):123-131 [FREE Full text] [CrossRef] [Medline]
- Hindley D. “More Than Just a Run in the Park”: An Exploration of Parkrun as a Shared Leisure Space. Leisure Sciences 2018 Jan 10;1:1-21. [CrossRef]
- Stevinson C, Wiltshire G, Hickson M. Facilitating participation in health-enhancing physical activity: a qualitative study of parkrun. Int J Behav Med 2015 Apr;22(2):170-177. [CrossRef] [Medline]
- Stevinson C, Hickson M. Exploring the public health potential of a mass community participation event. J Public Health (Oxf) 2014 Jun;36(2):268-274. [CrossRef] [Medline]
- WebMD. 2018. Types of diabetes mellitus URL: https://www.webmd.com/diabetes/guide/types-of-diabetes-mellitus#1 [accessed 2018-10-11]
- Boden G, Sargrad K, Homko C, Mozzoli M. Short-term effects of low-carbohydrate diet compared with usual diet in obese patients with type 2 diabetes. Ann Intern Med 2005 Mar 15;142(6):I44. [CrossRef] [Medline]
- Turner R, Holman R, Frighi V, Manley S, Matthews D, Neil A, et al. Tight blood pressure control risk of macrovascular and microvascular complications in type 2 diabetes: UKPDS 38. Br Med J 1998;317(7160):703. [Medline]
- The IBS Network. 2018. What is IBS? URL: https://www.theibsnetwork.org [accessed 2018-08-02]
- Canavan C, West J, Card T. The epidemiology of irritable bowel syndrome. Clin Epidemiol 2014;6:71-80 [FREE Full text] [CrossRef] [Medline]
- Drossman Z, Li Z, Andruzzi E, Temple RD, Talley NJ, Thompson WG, et al. U.S. householder survey of functional gastrointestinal disorders. Prevalence, sociodemography, and health impact. Dig Dis Sci 1993 Sep;38(9):1569-1580. [CrossRef] [Medline]
- Braun V, Clarke V. Using thematic analysis in psychology. Qualitative Research in Psychology 2006 Jan;3(2):77-101. [CrossRef]
- Halmos E, Power V, Shepherd S, Gibson P, Muir J. A diet low in FODMAPs reduces symptoms of irritable bowel syndrome. Gastroenterology 2014 Jan;146(1):67-75.e5. [CrossRef] [Medline]
- Rapp A, Tirassa M. Know Thyself: A Theory of the Self for Personal Informatics. Human–Computer Interaction 2017 Jan 27;32(5-6):335-380. [CrossRef]
- Ohlin F, Olsson C. Beyond a utility view of personal informatics: A postphenomenological framework. In: Adjunct Proceedings of the 2015 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2015 ACM International Symposium on Wearable Computers.: ACM; 2015 Presented at: the 2015 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2015 ACM International Symposium on Wearable Computers; September 07 – 11, 2015; Osaka, Japan p. 1087-1092. [CrossRef]
- Lloyd A. Framing information literacy as information practice: site ontology and practice theory. Journal of Documentation 2010 Mar 09;66(2):245-258. [CrossRef]
- Jimoh F, Lund EK, Harvey LJ, Frost C, Lay WJ, Roe MA, et al. Comparing Diet and Exercise Monitoring Using Smartphone App and Paper Diary: A Two-Phase Intervention Study. JMIR Mhealth Uhealth 2018 Jan 15;6(1):e17 [FREE Full text] [CrossRef] [Medline]
- Régnier F, Chauvel L. Digital Inequalities in the Use of Self-Tracking Diet and Fitness Apps: Interview Study on the Influence of Social, Economic, and Cultural Factors. JMIR Mhealth Uhealth 2018 Apr 20;6(4):e101 [FREE Full text] [CrossRef] [Medline]
- Mahmood K. Do People overestimate their information literacy skills? A systematic review of empirical evidence on the Dunning-Kruger effect. Commun Inf Lit 2016;10(2):199-213. [CrossRef]