Virtual dietitian as a precision nutrition application for gym and fitness enthusiasts: A quality improvement initiative
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Аннотации
The Virtual Dietitian (VD) application is a nutrition knowledge-based system that generates personalized meal plans in accordance with the one-size-does-not-fit-all concept of precision nutrition. A subset of the population that was not involved in its four-part developmental study was gym and fitness enthusiasts despite them being important target users. As part of our quality improvement (QI) plan, we initiated a two-phase user testing to inform modifications to VD. We recruited a total of 30 users with prior experience in nutrition applications. In phase 1, they used the current version of VD for a week and answered a mixed-form questionnaire afterward. We used the same questionnaire from our previous study, which is composed of System Usability Scale (SUS) items and open-ended questions. After months of system modification, the same set of users evaluated again the new VD version after another week of use. A paired-sample t-test showed a statistically significant difference in SUS scores before (SUS = 79) and after (SUS = 82) modifying VD based on the suggestions of the participants (p = 0.005). Some new features include water tracker and reminder modules, Google Fit integration, and other nutrition support services (e.g., teleconsultation with registered dietitians). Although further refinements to VD are still needed, we were able to incorporate a QI initiative typically employed by healthcare organizations into software development for a better and improved personalized nutrition application.
Recommended Citation
Garcia, M. B., Revano, T. F., Loresco P. J. M., Maaliw, R. R., Oducado, R. M. F., & Uludag K. (2022). Virtual dietitian as a precision nutrition application for gym and fitness enthusiasts: A quality improvement initiative. IEEE 14th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment and Management (HNICEM) (pp. 1-12). IEEE. https://doi.org/10.1109/HNICEM57413.2022.10109490
Type
Conference paperISSN
2770-0682ISBN
9781665464932Keywords
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