Multi-Criteria Usability Evaluation of mHealth Applications on Type 2 Diabetes Mellitus Using Two Hybrid MCDM Models: CODAS-FAHP and MOORA-FAHP

Simple Summary Considering the world's present pandemic situation, mHealth applications are essential for self-management of health. However, the recent growth of the healthcare industry provides various mHealth applications that result in difficulties for ordinary people in selecting the best application to fulfill their needs to their satisfaction. This research paper focuses on developing two hybrid decision-making methods, CODAS-FAHP and MOORA-FAHP, which may be used in assessing the usability of mHealth applications to monitor type 2 diabetes mellitus (T2DM) patients. The resulting analysis with the two hybrid models shows that the selection of mHealth applications can be done efficiently. People use mHealth applications to help manage and keep track of their health conditions more effectively. With the increase of mHealth applications, it has become more difficult to choose the best applications that are user-friendly and provide user satisfaction. The best techniques for any decision-making challenge are multi-criteria decision-making (MCDM) methodologies. However, traditional MCDM methods cannot provide accurate results in complex situations. Currently, researchers are focusing on the use of hybrid MCDM methods to provide accurate decisions for complex problems. Thus, the authors in this paper proposed two hybrid MCDM methods, CODAS-FAHP and MOORA-FAHP, to assess the usability of the five most familiar mHealth applications that focus on type 2 diabetes mellitus (T2DM), based on ten criteria. The fuzzy Analytic Hierarchy Process (FAHP) is applied for efficient weight estimation by removing the vagueness and ambiguity of expert judgment. The CODAS and MOORA MCDM methods are used to rank the mHealth applications, depending on the usability parameter, and to select the best application. The resulting analysis shows that the ranking from both hybrid models is sufficiently consistent. To assess the proposed framework's stability and validity, a sensitivity analysis was performed. It showed that the result is consistent with the proposed hybrid model.

Automated summary

Considering the current global pandemic situation, mHealth applications play a crucial role in self-management of health. However, the increasing availability of healthcare applications has made it challenging for individuals to select the most suitable application that meets their needs and satisfaction. This research focuses on developing two hybrid decision-making methods to assess the usability of mHealth applications for monitoring type 2 diabetes mellitus patients. The results show that the selection of mHealth applications can be efficiently done using these hybrid models.