Biswas_et_al_2021.pdf (1.54 MB)
ACCU3RATE: A mobile health application rating scale based on user reviews
journal contribution
posted on 2023-07-26, 15:37 authored by Milon Biswas, Marzia Hoque Tania, M. Shamim Kaiser, Russell Kabir, Mufti Mahmud, Atika A. KemalBackground-
Over the last decade, mobile health applications (mHealth App) have evolved exponentially to assess and support our health and well-being.
Objective-
This paper presents an Artificial Intelligence (AI)-enabled mHealth app rating tool, called ACCU3RATE, which takes multidimensional measures such as user star rating, user review and features declared by the developer to generate the rating of an app. However, currently, there is very little conceptual understanding on how user reviews affect app rating from a multi-dimensional perspective. This study applies AI-based text mining technique to develop more comprehensive understanding of user feedback based on several important factors, determining the mHealth app ratings.
Method-
Based on the literature, six variables were identified that influence the mHealth app rating scale. These factors are user star rating, user text review, user interface (UI) design, functionality, security and privacy, and clinical approval. Natural Language Toolkit package is used for interpreting text and to identify the App users’ sentiment. Additional considerations were accessibility, protection and privacy, UI design for people living with physical disability. Moreover, the details of clinical approval, if exists, were taken from the developer’s statement. Finally, we fused all the inputs using fuzzy logic to calculate the new app rating score.
Results and conclusions-
ACCU3RATE concentrates on heart related Apps found in the play store and App gallery. The findings indicate the efficacy of the proposed method as opposed to the current device scale. This study has implications for both App developers and consumers who are using mHealth Apps to monitor and track their health. The performance evaluation shows that the proposed mHealth scale has shown excellent reliability as well as internal consistency of the scale, and high inter-rater reliability index. It has also been noticed that the fuzzy based rating scale, as in ACCU3RATE, matches more closely to the rating performed by experts.
History
Refereed
- Yes
Volume
16Issue number
12Page range
e0258050Publication title
PLOS ONEISSN
1932-6203External DOI
Publisher
Public Library of ScienceFile version
- Published version
Language
- eng
Official URL
Legacy posted date
2021-12-20Legacy creation date
2021-12-18Legacy Faculty/School/Department
Faculty of Health, Education, Medicine & Social CareUsage metrics
Categories
No categories selectedKeywords
Licence
Exports
RefWorks
BibTeX
Ref. manager
Endnote
DataCite
NLM
DC