Anglia Ruskin Research Online (ARRO)
Browse
Biswas_et_al_2021.pdf (1.54 MB)

ACCU3RATE: A mobile health application rating scale based on user reviews

Download (1.54 MB)
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. Kemal
Background- 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

16

Issue number

12

Page range

e0258050

Publication title

PLOS ONE

ISSN

1932-6203

Publisher

Public Library of Science

File version

  • Published version

Language

  • eng

Legacy posted date

2021-12-20

Legacy creation date

2021-12-18

Legacy Faculty/School/Department

Faculty of Health, Education, Medicine & Social Care

Usage metrics

    ARU Outputs

    Categories

    No categories selected

    Licence

    Exports

    RefWorks
    BibTeX
    Ref. manager
    Endnote
    DataCite
    NLM
    DC