research-article

Rasch-based tailored goals for nutrition assistance systems

Authors:

Hanna Schäfer,

Martijn C. WillemsenAuthors Info & Claims

IUI '19: Proceedings of the 24th International Conference on Intelligent User Interfaces

Pages 18 - 29

https://doi.org/10.1145/3301275.3302298

Published: 17 March 2019 Publication History

Abstract

Choosing adequate goals plays is central to the success of a task. With this study, we investigate tailoring the goals of a nutrition assistance system to the user's abilities according to a Rasch scale. To that end, we evaluated two versions of a mobile system that offers dietary tracking, visual feedback, and personalized recipe recommendations. The original version targets optimal nutritional behavior and focuses on the six least optimal nutrients (N=51). The adapted version targets only improved nutritional behavior compared to the status quo and thus tailors the advice to the next six achievable nutrients according to a Rasch scale (N=47). Results of the two-week study indicate that the tailored advice leads to higher success for the focused nutrients, and is perceived to be more diverse and personalized, and thus more effective.

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Rasch-based tailored goals for nutrition assistance systems

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cover image ACM Conferences

IUI '19: Proceedings of the 24th International Conference on Intelligent User Interfaces

March 2019

713 pages

ISBN:9781450362726

DOI:10.1145/3301275

General Chairs:
Wai-Tat Fu,
Shimei Pan,
Program Chairs:
Oliver Brdiczka,
Polo Chau,
Gaelle Calvary

Copyright © 2019 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 17 March 2019

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German Ministry for Education and Research (BMBF)

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IUI '19: 24th International Conference on Intelligent User Interfaces

March 17 - 20, 2019

California, Marina del Ray

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IUI '19 Paper Acceptance Rate 71 of 282 submissions, 25%;

Overall Acceptance Rate 746 of 2,811 submissions, 27%

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Cited By

Yera RAlzahrani AMartínez LRodríguez R(2023)A Systematic Review on Food Recommender Systems for Diabetic PatientsInternational Journal of Environmental Research and Public Health10.3390/ijerph2005424820:5(4248)Online publication date: 27-Feb-2023
https://doi.org/10.3390/ijerph20054248
Starke AAsotic ETrattner CVan Loo E(2023)Examining the User Evaluation of Multi-List Recommender Interfaces in the Context of Healthy Recipe ChoicesACM Transactions on Recommender Systems10.1145/35819301:4(1-31)Online publication date: 24-Feb-2023
https://dl.acm.org/doi/10.1145/3581930
Liang YPonnada ALamere PDaskalova N(2023)Enabling Goal-Focused Exploration of Podcasts in Interactive Recommender SystemsProceedings of the 28th International Conference on Intelligent User Interfaces10.1145/3581641.3584032(142-155)Online publication date: 27-Mar-2023
https://dl.acm.org/doi/10.1145/3581641.3584032
Starke AMusto CRapp ASemeraro GTrattner C(2023)“Tell Me Why”: using natural language justifications in a recipe recommender system to support healthier food choicesUser Modeling and User-Adapted Interaction10.1007/s11257-023-09377-834:2(407-440)Online publication date: 24-Oct-2023
https://doi.org/10.1007/s11257-023-09377-8
Torkamaan HZiegler J(2022)Recommendations as Challenges: Estimating Required Effort and User Ability for Health Behavior Change RecommendationsProceedings of the 27th International Conference on Intelligent User Interfaces10.1145/3490099.3511118(106-119)Online publication date: 22-Mar-2022
https://dl.acm.org/doi/10.1145/3490099.3511118
Balakrishna CGanesh TKhosla A(2021)NutrifyHandbook of Research on Solving Modern Healthcare Challenges With Gamification10.4018/978-1-7998-7472-0.ch015(279-292)Online publication date: 2021
https://doi.org/10.4018/978-1-7998-7472-0.ch015
Wang YKönig LReiterer H(2021)A Smartphone App to Support Sedentary Behavior Change by Visualizing Personal Mobility Patterns and Action Planning (SedVis): Development and Pilot StudyJMIR Formative Research10.2196/153695:1(e15369)Online publication date: 27-Jan-2021
https://doi.org/10.2196/15369
Starke AWillemsen MSnijders C(2021)Using Explanations as Energy-Saving Frames: A User-Centric Recommender StudyAdjunct Proceedings of the 29th ACM Conference on User Modeling, Adaptation and Personalization10.1145/3450614.3464477(229-237)Online publication date: 21-Jun-2021
https://dl.acm.org/doi/10.1145/3450614.3464477
Musto CStarke ATrattner CRapp ASemeraro G(2021)Exploring the Effects of Natural Language Justifications in Food Recommender SystemsProceedings of the 29th ACM Conference on User Modeling, Adaptation and Personalization10.1145/3450613.3456827(147-157)Online publication date: 21-Jun-2021
https://dl.acm.org/doi/10.1145/3450613.3456827
Hauptmann HLeipold NMadenach MWintergerst MLurz MGroh GBöhm MGedrich KKrcmar H(2021)Effects and challenges of using a nutrition assistance system: results of a long-term mixed-method studyUser Modeling and User-Adapted Interaction10.1007/s11257-021-09301-y32:5(923-975)Online publication date: 15-Oct-2021
https://doi.org/10.1007/s11257-021-09301-y
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