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Title: Crowdsourcing users’ comments for clinical and operational features analysis of diabetes mobile apps.
Epworth Authors: Wickramasinghe, Nilmini
Other Authors: Ossai, Chinedau
Keywords: Diabetes
Data Analytics
Decision Support
Diabetes Mobile Apps
Health Informatics Clinical Institute, Epworth HealthCare, Victoria, Australia
Issue Date: 5-Jan-2021
Conference Name: 54th HICSS 2021 (Hawaii International conference on System Sciences)
Conference Location: Maui, Hawaii USA
Abstract: Today there exist a plethora of mobile apps focused on diabetes self-management. To understand the rate of inclusion and influences of these numerous diabetes mobile apps (DMAS), we crowdsourced and analyzed negative users’ comments and the design features of numerous apps, underpinned by fit viability as the theoretical analysis lens. Thus, by concentrating our efforts on apps written in English collected from google play and apple app store, we identified and classified DMAS as a health monitoring app (HMAS) and information repository apps (IRAS), and statistically determined the effects of different diabetes self-management indicators on their functionalities. Our results affirm that these solutions have limited functionalities to facilitate self-management of diabetes due to poor design which hinders intelligent decision support, as well as limits inclusion and performance of wellness support features. In addition, many of these apps are also operationally inefficient.
DOI: 10.24251/HICSS.2021.428
Type: Conference Paper
Affiliated Organisations: Swinburne University of Technology, Australia
Appears in Collections:Health Informatics

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