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The Typology of Digital Health Apps According to their Quality Scores and User Ratings: K-Means Clustering

Published: 21 September 2023 Publication History

Abstract

This study focuses on discovering the types of digital health apps that exist in accordance with several quality characteristics and their user ratings on app stores. The quality scores include scores for the app's user experience (UX), its data privacy (DP) and professional clinical assurance (PCA) which are scores provided by ORCHA that use many objective questions to quality assess health apps (ORCHA stands for The Organisation for the Review of Care and Health Apps). K-means clustering has been used to group many digital health apps (n>1700) that have similar traits. We describe 6 different types of digital health apps. This study shows that one cluster (or type) comprise of 23.8% of health apps which typically have good user ratings and high-quality scores. Another cluster of apps comprise of 27.2% of health apps, which typically have low PCA scores but high UX and DP scores with good user ratings, indicating that this cluster of health apps are held back by their PCA score from becoming ‘the highest quality’ health apps.

References

[1]
Huckvale, K. 2020. Smartphone apps for the treatment of mental health conditions: status and considerations. Current Opinion in Psychology. 36, (Dec. 2020), 65–70.
[2]
Kern, J. 2021. written consent of IQVIA and the IQVIA Institute. Digital Health Trends. (2021).
[3]
Larsen, M.E. 2016. A Systematic Assessment of Smartphone Tools for Suicide Prevention. PLoS ONE. 11, 4 (Apr. 2016).
[4]
Mathews, S.C. 2019. Digital health: a path to validation. npj Digital Medicine 2019 2:1. 2, 1 (May 2019), 1–9.
[5]
ORCHA Privacy Policy: https://appfinder.orcha.co.uk/privacy-policy/. Accessed: 2022-08-11.
[6]
Review Documentation - Review Development & Resources | Exte: https://confluence.external-share.com/content/b6055aac-83e4-4947-be0e-ebb8c39559ef. Accessed: 2022-03-13.

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      ECCE '23: Proceedings of the European Conference on Cognitive Ergonomics 2023
      September 2023
      189 pages
      ISBN:9798400708756
      DOI:10.1145/3605655
      Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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      Association for Computing Machinery

      New York, NY, United States

      Publication History

      Published: 21 September 2023

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      Author Tags

      1. cluster analysis
      2. digital health apps
      3. mHealth quality traits

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      • Work in progress
      • Research
      • Refereed limited

      Conference

      ECCE 2023
      ECCE 2023: European Conference in Cognitive Ergonomics
      September 19 - 22, 2023
      Swansea, United Kingdom

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      Overall Acceptance Rate 56 of 91 submissions, 62%

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