Where Should Mobile Health Application Providers Focus Their Goals?

Authors

Xiaojia Wang^1, , Kuo Du¹, Keyu Zhu^{1, *,} , Shen Xu¹, Shanshan Zhang^{2, 3}

¹Department of Information Management, School of Management, Hefei University of Technology, Hefei, Anhui, China, 230009

²Department of Clinical Teaching, The First Affiliated Hospital of Anhui University of Chinese Medicine, Hefei, Anhui, China, 230031

³The National Chinese Medicine Clinical Research Base—Key Disease of Diabetes Mellitus Study, Hefei, Anhui, China, 230031

^*Corresponding author. Email: zhukeyu@hfut.edu.cn

DOI

10.2991/ijcis.d.210305.001How to use a DOI?

Keywords

Service evaluation; Mobile health application; Domain-adaptive; Machine learning; Delphi

Abstract

In the context of “Internet +” medical treatment, mobile health applications provide services for people in a new way, making it possible for people to carry out health management anytime and anywhere. According to the survey data, the most powerful consumers in the field of mobile health applications are those aged 24 to 35. Thus, it is particularly important to study the preferences of young people for mobile health applications. Therefore, this study established a domain-adaptive mobile health application evaluation model based on users' experience, and used an interactive algorithm combining machine learning and Delphi method to calculate the weight distribution of evaluation factors. Compared with previous studies, the evaluation index based on user experience of youth group is established. On the one hand, we have a targeted understanding of the use characteristics of the youth group and subdivide the market of mobile health applications; on the other hand, we establish evaluation indexes based on user experience, which is more in line with the customer-oriented product service concept. At the same time, the mobile health application evaluation system established in this study adopts human-computer interaction, which can not only ensure efficiency, but also add expertise in the field to make the results more accurate.

Copyright

© 2021 The Authors. Published by Atlantis Press B.V.

Open Access

This is an open access article distributed under the CC BY-NC 4.0 license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - JOUR
AU  - Xiaojia Wang
AU  - Kuo Du
AU  - Keyu Zhu
AU  - Shen Xu
AU  - Shanshan Zhang
PY  - 2021
DA  - 2021/03/12
TI  - Where Should Mobile Health Application Providers Focus Their Goals?
JO  - International Journal of Computational Intelligence Systems
SP  - 1119
EP  - 1131
VL  - 14
IS  - 1
SN  - 1875-6883
UR  - https://doi.org/10.2991/ijcis.d.210305.001
DO  - 10.2991/ijcis.d.210305.001
ID  - Wang2021
ER  -