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

Kamaldeep Gupta, Sharmistha Roy, Ayman Altameem, Raghvendra Kumar, Abdul Khader Jilani Saudagar and Ramesh Chandra Poonia
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Kamaldeep Gupta: Faculty of Computing and Information Technology, Usha Martin University, Ranchi 835103, India
Sharmistha Roy: Faculty of Computing and Information Technology, Usha Martin University, Ranchi 835103, India
Ayman Altameem: Department of Computer Science and Engineering, College of Applied Studies and Community Services, King Saud University, Riyadh 11533, Saudi Arabia
Raghvendra Kumar: Department of Computer Science and Engineering, GIET University, Rayagada 765022, India
Abdul Khader Jilani Saudagar: Information Systems Department, Imam Mohammad Ibn Saud Islamic University (IMSIU), Riyadh 11432, Saudi Arabia
Ramesh Chandra Poonia: Department of Computer Science, CHRIST (Deemed to be University), Bangalore 560029, India

IJERPH, 2022, vol. 19, issue 12, 1-28

Abstract: 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.

Keywords: MARS; ID3; mHealth applications; T2DM; usability; decision making (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2022
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