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Computer Science > Computers and Society

arXiv:1904.08376 (cs)
[Submitted on 17 Apr 2019]

Title:Comparison of Self-monitoring Feedback Data from Electronic Food and Nutrition Tracking Tools

Authors:Ahmed Fadhil
View a PDF of the paper titled Comparison of Self-monitoring Feedback Data from Electronic Food and Nutrition Tracking Tools, by Ahmed Fadhil
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Abstract:Changing dietary habits and keeping food diary encourages fewer calorie consumption, and thus weight loss. Studies have shown that people who keep food diary are more successful in losing weight and keeping it off. However, no study has investigated the nutritional values produced by food journaling applications. This is crucial since keeping food diaries helps identify areas where changes needed to help user's loss weight, based on the application feedback. To achieve this, the provided data should be consistent among all applications. Otherwise, this will question the effectiveness and reliability of such tools in tracking diet and weight loss, and hence question user trust in these applications. This study characterizes the use of 4 food journaling applications to track user diet for 10 days (namely, MyFitnessPal, Lose It, FatSecret, CRONOMeter). We measured variations between the output of each application. The findings revealed an inconsistent and a variation in the output feedback given by all the 4 tools. Although some tools provided closer values, still their data were different and inconsistent. Moreover, some tools were missing essential nutritional fact data, such as sugar and fiber. We additionally compared a sample of food items common among all tools with the Swiss Food Composition Database and checked for their consistency with the same items in the database. The evaluation of the applications showed a gap in the data consistency among applications and the FCD, and questions how reliable they are for food logging and diet tracking. This study contributes to current research in health and wellbeing and can be referenced by researchers to provide deeper insights into the data consistency. Future work should examine ways to provide precise output that is common among all applications, so to guarantee the effect on weight loss.
Subjects: Computers and Society (cs.CY)
Cite as: arXiv:1904.08376 [cs.CY]
  (or arXiv:1904.08376v1 [cs.CY] for this version)
  https://doi.org/10.48550/arXiv.1904.08376
arXiv-issued DOI via DataCite

Submission history

From: Ahmed Fadhil Dr. [view email]
[v1] Wed, 17 Apr 2019 17:22:08 UTC (3,507 KB)
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