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

Maciej Hyzy; RR Bond; Maurice Mulvenna; Lu Bai; Simon Leigh

doi:10.1145/3605655.3605786

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

Maciej Hyzy, RR Bond, Maurice Mulvenna, Lu Bai, Simon Leigh

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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.

Original language	English
Title of host publication	Proceedings of the European Conference on Cognitive Ergonomics 2023
Subtitle of host publication	ECCE '23
Editors	Alan Dix, Irene Reppa, Carina Westling, Harry Witchel
Place of Publication	New York
Publisher	Association for Computing Machinery
Pages	1-4
Number of pages	4
ISBN (Electronic)	979-8-4007-0875-6
DOIs	https://doi.org/10.1145/3605655.3605786
Publication status	Published (in print/issue) - 21 Sept 2021
Event	European Conference in Cognitive Ergonomics - Swansea University, Swansea Duration: 19 Sept 2023 → 22 Sept 2023 https://digitaleconomy.wales/ecce2023/workshops/

Publication series

Name	Proceedings of the European Conference on Cognitive Ergonomics 2023
Publisher	Association for Computing Machinery

Conference

Conference	European Conference in Cognitive Ergonomics
Abbreviated title	ECCE
City	Swansea
Period	19/09/23 → 22/09/23
Internet address	https://digitaleconomy.wales/ecce2023/workshops/

Keywords

mHealth quality traits
cluster analysis
digital health apps

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1145/3605655.3605786

Cite this

Hyzy, M., Bond, RR., Mulvenna, M., Bai, L., & Leigh, S. (2021). The Typology of Digital Health Apps According to their Quality Scores and User Ratings: K-Means Clustering. In A. Dix, I. Reppa, C. Westling, & H. Witchel (Eds.), Proceedings of the European Conference on Cognitive Ergonomics 2023: ECCE '23 (pp. 1-4). Article 20 (Proceedings of the European Conference on Cognitive Ergonomics 2023). Association for Computing Machinery. https://doi.org/10.1145/3605655.3605786

Hyzy, Maciej ; Bond, RR ; Mulvenna, Maurice et al. / The Typology of Digital Health Apps According to their Quality Scores and User Ratings : K-Means Clustering. Proceedings of the European Conference on Cognitive Ergonomics 2023: ECCE '23. editor / Alan Dix ; Irene Reppa ; Carina Westling ; Harry Witchel. New York : Association for Computing Machinery, 2021. pp. 1-4 (Proceedings of the European Conference on Cognitive Ergonomics 2023).

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

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{\textquoteright}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 {\textquoteleft}the highest quality{\textquoteright} health apps.",

keywords = "mHealth quality traits, cluster analysis, digital health apps",

author = "Maciej Hyzy and RR Bond and Maurice Mulvenna and Lu Bai and Simon Leigh",

year = "2021",

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doi = "10.1145/3605655.3605786",

language = "English",

series = "Proceedings of the European Conference on Cognitive Ergonomics 2023",

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editor = "Alan Dix and Irene Reppa and Carina Westling and Harry Witchel",

booktitle = "Proceedings of the European Conference on Cognitive Ergonomics 2023",

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Hyzy, M , Bond, RR , Mulvenna, M, Bai, L & Leigh, S 2021, The Typology of Digital Health Apps According to their Quality Scores and User Ratings: K-Means Clustering. in A Dix, I Reppa, C Westling & H Witchel (eds), Proceedings of the European Conference on Cognitive Ergonomics 2023: ECCE '23., 20, Proceedings of the European Conference on Cognitive Ergonomics 2023, Association for Computing Machinery, New York, pp. 1-4, European Conference in Cognitive Ergonomics, Swansea , 19/09/23. https://doi.org/10.1145/3605655.3605786

The Typology of Digital Health Apps According to their Quality Scores and User Ratings: K-Means Clustering. / Hyzy, Maciej ; Bond, RR ; Mulvenna, Maurice et al.
Proceedings of the European Conference on Cognitive Ergonomics 2023: ECCE '23. ed. / Alan Dix; Irene Reppa; Carina Westling; Harry Witchel. New York: Association for Computing Machinery, 2021. p. 1-4 20 (Proceedings of the European Conference on Cognitive Ergonomics 2023).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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T1 - The Typology of Digital Health Apps According to their Quality Scores and User Ratings

T2 - European Conference in Cognitive Ergonomics

AU - Hyzy, Maciej

AU - Bond, RR

AU - Mulvenna, Maurice

AU - Bai, Lu

AU - Leigh, Simon

PY - 2021/9/21

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N2 - 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.

AB - 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.

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KW - digital health apps

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DO - 10.1145/3605655.3605786

M3 - Conference contribution

T3 - Proceedings of the European Conference on Cognitive Ergonomics 2023

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BT - Proceedings of the European Conference on Cognitive Ergonomics 2023

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Y2 - 15 September 2017 through 22 September 2023

ER -

Hyzy M , Bond RR , Mulvenna M, Bai L, Leigh S. The Typology of Digital Health Apps According to their Quality Scores and User Ratings: K-Means Clustering. In Dix A, Reppa I, Westling C, Witchel H, editors, Proceedings of the European Conference on Cognitive Ergonomics 2023: ECCE '23. New York: Association for Computing Machinery. 2021. p. 1-4. 20. (Proceedings of the European Conference on Cognitive Ergonomics 2023). doi: 10.1145/3605655.3605786

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

Abstract

Publication series

Conference

Keywords

UN SDGs

Access to Document

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Cite this