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Usability Evaluation and Classification of mHealth Applications for Type 2 Diabetes Mellitus Using MARS and ID3 Algorithm

The rapid growth of mHealth applications for Type 2 Diabetes Mellitus (T2DM) patients’ self-management has motivated the evaluation of these applications from both the usability and user point of view. The objective of this study was to identify mHealth applications that focus on T2DM from the Andro...

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Autores principales: Gupta, Kamaldeep, Roy, Sharmistha, Altameem, Ayman, Kumar, Raghvendra, Saudagar, Abdul Khader Jilani, Poonia, Ramesh Chandra
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9222518/
https://www.ncbi.nlm.nih.gov/pubmed/35742248
http://dx.doi.org/10.3390/ijerph19126999
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author Gupta, Kamaldeep
Roy, Sharmistha
Altameem, Ayman
Kumar, Raghvendra
Saudagar, Abdul Khader Jilani
Poonia, Ramesh Chandra
author_facet Gupta, Kamaldeep
Roy, Sharmistha
Altameem, Ayman
Kumar, Raghvendra
Saudagar, Abdul Khader Jilani
Poonia, Ramesh Chandra
author_sort Gupta, Kamaldeep
collection PubMed
description The rapid growth of mHealth applications for Type 2 Diabetes Mellitus (T2DM) patients’ self-management has motivated the evaluation of these applications from both the usability and user point of view. The objective of this study was to identify mHealth applications that focus on T2DM from the Android store and rate them from the usability perspective using the MARS tool. Additionally, a classification of these mHealth applications was conducted using the ID3 algorithm to identify the most preferred application. The usability of the applications was assessed by two experts using MARS. A total of 11 mHealth applications were identified from the initial search, which fulfilled our inclusion criteria. The usability of the applications was rated using the MARS scale, from 1 (inadequate) to 5 (excellent). The Functionality (3.23) and Aesthetics (3.22) attributes had the highest score, whereas Information (3.1) had the lowest score. Among the 11 applications, “mySugr” had the highest average MARS score for both Application Quality (4.1/5) as well as Application Subjective Quality (4.5/5). Moreover, from the classification conducted using the ID3 algorithm, it was observed that 6 out of 11 mHealth applications were preferred for the self-management of T2DM.
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spelling pubmed-92225182022-06-24 Usability Evaluation and Classification of mHealth Applications for Type 2 Diabetes Mellitus Using MARS and ID3 Algorithm Gupta, Kamaldeep Roy, Sharmistha Altameem, Ayman Kumar, Raghvendra Saudagar, Abdul Khader Jilani Poonia, Ramesh Chandra Int J Environ Res Public Health Article The rapid growth of mHealth applications for Type 2 Diabetes Mellitus (T2DM) patients’ self-management has motivated the evaluation of these applications from both the usability and user point of view. The objective of this study was to identify mHealth applications that focus on T2DM from the Android store and rate them from the usability perspective using the MARS tool. Additionally, a classification of these mHealth applications was conducted using the ID3 algorithm to identify the most preferred application. The usability of the applications was assessed by two experts using MARS. A total of 11 mHealth applications were identified from the initial search, which fulfilled our inclusion criteria. The usability of the applications was rated using the MARS scale, from 1 (inadequate) to 5 (excellent). The Functionality (3.23) and Aesthetics (3.22) attributes had the highest score, whereas Information (3.1) had the lowest score. Among the 11 applications, “mySugr” had the highest average MARS score for both Application Quality (4.1/5) as well as Application Subjective Quality (4.5/5). Moreover, from the classification conducted using the ID3 algorithm, it was observed that 6 out of 11 mHealth applications were preferred for the self-management of T2DM. MDPI 2022-06-08 /pmc/articles/PMC9222518/ /pubmed/35742248 http://dx.doi.org/10.3390/ijerph19126999 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Gupta, Kamaldeep
Roy, Sharmistha
Altameem, Ayman
Kumar, Raghvendra
Saudagar, Abdul Khader Jilani
Poonia, Ramesh Chandra
Usability Evaluation and Classification of mHealth Applications for Type 2 Diabetes Mellitus Using MARS and ID3 Algorithm
title Usability Evaluation and Classification of mHealth Applications for Type 2 Diabetes Mellitus Using MARS and ID3 Algorithm
title_full Usability Evaluation and Classification of mHealth Applications for Type 2 Diabetes Mellitus Using MARS and ID3 Algorithm
title_fullStr Usability Evaluation and Classification of mHealth Applications for Type 2 Diabetes Mellitus Using MARS and ID3 Algorithm
title_full_unstemmed Usability Evaluation and Classification of mHealth Applications for Type 2 Diabetes Mellitus Using MARS and ID3 Algorithm
title_short Usability Evaluation and Classification of mHealth Applications for Type 2 Diabetes Mellitus Using MARS and ID3 Algorithm
title_sort usability evaluation and classification of mhealth applications for type 2 diabetes mellitus using mars and id3 algorithm
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9222518/
https://www.ncbi.nlm.nih.gov/pubmed/35742248
http://dx.doi.org/10.3390/ijerph19126999
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