Selection of smartphone-based mobile applications for obesity management using an interval neutrosophic vague decision-making framework
The selection of mobile applications for managing obesity poses a complex multicriteria decision-making (MCDM) challenge. This complexity arises from the diverse criteria of the apps, their respective values, and the need to determine the relative importance of these criteria. Therefore, this study...
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| Main Authors: | , , , , , , , |
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Elsevier Ltd
2025
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| Summary: | The selection of mobile applications for managing obesity poses a complex multicriteria decision-making (MCDM) challenge. This complexity arises from the diverse criteria of the apps, their respective values, and the need to determine the relative importance of these criteria. Therefore, this study contributes to the body of knowledge by evaluating smartphone-based mobile applications for obesity management through the development of a novel MCDM selection framework. The decision matrix formulates the quality assessment criteria and identifies smartphone applications for diagnosing obesity. In the research methodology, the MCDM solution is presented by integrating two methods: the interval neutrosophic vague-based fuzzy-weighted zero-consistency (INV-FWZIC) method for weighting the quality assessment criteria and the interval neutrosophic vague-based fuzzy decision by opinion score method (INV-FDOSM) for selecting smartphone applications for obesity. The results indicate that the ?technology-enhanced features? and ?usability? criteria received the highest equal weight score (0.2183), while the criterion of ?behavior change techniques? received the lowest weight (0.1783). The group decision-making results show that Application A1 (Noom Weight Loss Coach) is the best, with a score of 0.6869, while Application A7 (Cronometer) is the worst, with the lowest score of 0.6165. Various assessment approaches, including systematic ranking, reliability and validity analyses, sensitivity analysis, and comparison analysis, are employed to evaluate and validate the proposed framework. ? 2024 Elsevier Ltd |
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