The Usability and Feasibility of a Dietary Intake Self-Monitoring Application in a Population with Varying Literacy Levels

People with different literacy skills can effectively use icon-based interfaces for portion size estimation and develop personalized usage patterns to self-regulate their fluid and dietary intakes. Moreover, they can experience an enhancement in their dietary self-efficacy skills by using a mobile application aimed at providing nutritional feedback. Furthermore, this research shows that the constructs of the ITHBC are effective in promoting dietary behavior change in a population with varying literacy skills. The target users can benefit from explicitly visualizing the relationship between their health outcomes and the factors influencing those outcomes. These user ambitions could be supported by developing machine learning models. Future research should also focus on enhancing the mechanisms by which technology can further enhance each component of the ITHBC framework.

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Institutions

Publication Details

Journal
Journal of Personalized Medicine
Published
2024-09-20
DOI
https://doi.org/10.3390/jpm14091001
Citations
2
Primary Topic
Mobile Health and mHealth Applications
Type
article
Field-Weighted Citation Impact
1.70

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article

The Usability and Feasibility of a Dietary Intake Self-Monitoring Application in a Population with Varying Literacy Levels

Kay Connelly, Katie A. Siek, Beenish Moalla Chaudhry
2 citations
Journal of Personalized Medicine
Mobile Health and mHealth Applications
1.70
article

The Usability and Feasibility of a Dietary Intake Self-Monitoring Application in a Population with Varying Literacy Levels

Kay Connelly, Katie A. Siek, Beenish Moalla Chaudhry
article en
2 citations

Abstract

People with different literacy skills can effectively use icon-based interfaces for portion size estimation and develop personalized usage patterns to self-regulate their fluid and dietary intakes. Moreover, they can experience an enhancement in their dietary self-efficacy skills by using a mobile application aimed at providing nutritional feedback. Furthermore, this research shows that the constructs of the ITHBC are effective in promoting dietary behavior change in a population with varying literacy skills. The target users can benefit from explicitly visualizing the relationship between their health outcomes and the factors influencing those outcomes. These user ambitions could be supported by developing machine learning models. Future research should also focus on enhancing the mechanisms by which technology can further enhance each component of the ITHBC framework.

Journal of Personalized MedicineVol. 14(9)
Indiana University Bloomington (US), University of Louisiana at Lafayette (US), Michigan State University (US)
Purdue University
Quality Education
Openalex Percentile: Top 14%
Mobile Health and mHealth Applications
1.70
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