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建立高血压管理应用用户满意度评估指标体系:结合用户生成内容和层次分析法。

Establishing an Evaluation Indicator System for User Satisfaction With Hypertension Management Apps: Combining User-Generated Content and Analytic Hierarchy Process.

机构信息

Center for Health Policy Studies, School of Public Health, Zhejiang University, Hangzhou, China.

Department of Cardiology, Second Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, China.

出版信息

J Med Internet Res. 2024 Sep 3;26:e60773. doi: 10.2196/60773.

DOI:10.2196/60773
PMID:39226103
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11408894/
Abstract

BACKGROUND

Hypertension management apps (HMAs) can be effective in controlling blood pressure, but their actual impact is often suboptimal. Establishing a user satisfaction evaluation indicator system for HMAs can assist app developers in enhancing app design and functionality, while also helping users identify apps that best meet their needs. This approach aims to improve the overall effectiveness of app usage.

OBJECTIVE

This study aims to systematically collect data on HMAs and their user reviews in the United States and China. It analyzes app usage patterns and functional characteristics, identifies factors influencing user satisfaction from existing research, and develops a satisfaction evaluation indicator system to provide more accurate recommendations for improving user satisfaction.

METHODS

We conducted a descriptive statistical analysis to assess the development status of HMAs in both countries and applied the task-technology fit model to evaluate whether the app functionalities align with business needs. We separately summarized the factors influencing user satisfaction in both countries from previous research, utilized the analytic hierarchy process to develop an evaluation indicator system for HMA user satisfaction, and calculated satisfaction levels. Based on these findings, we propose improvements to enhance app functionality and user satisfaction.

RESULTS

In terms of current development status, there were fewer HMAs and user reviews in China compared with the United States. Regarding app functional availability, fewer than 5% (4/91) of the apps achieved a demand fulfillment rate exceeding 80% (8/10). Overall, user satisfaction in both countries was low.

CONCLUSIONS

In the United States, user satisfaction was lowest for advertising distribution, data synchronization, and reliability. By contrast, Chinese apps need improvements in cost efficiency and compatibility.

摘要

背景

高血压管理应用程序(HMAs)在控制血压方面可能非常有效,但它们的实际效果往往并不理想。建立 HMA 用户满意度评估指标体系可以帮助应用程序开发者增强应用程序设计和功能,同时帮助用户识别最符合其需求的应用程序。这种方法旨在提高应用程序使用的整体效果。

目的

本研究旨在系统地收集美国和中国的 HMA 及其用户评价数据。它分析了应用程序的使用模式和功能特点,从现有研究中确定影响用户满意度的因素,并开发了一个满意度评估指标体系,为提高用户满意度提供更准确的建议。

方法

我们进行了描述性统计分析,以评估这两个国家 HMA 的发展状况,并应用任务-技术适配模型来评估应用程序功能是否符合业务需求。我们分别从以前的研究中总结了影响两国用户满意度的因素,利用层次分析法开发了一个 HMA 用户满意度评估指标体系,并计算了满意度水平。根据这些发现,我们提出了改进建议,以增强应用程序的功能和用户满意度。

结果

就当前的发展状况而言,中国的 HMA 和用户评价比美国少。就应用程序功能可用性而言,不足 5%(4/91)的应用程序的需求满足率超过 80%(8/10)。总的来说,两国用户的满意度都很低。

结论

在美国,用户对广告分发、数据同步和可靠性的满意度最低。相比之下,中国的应用程序需要提高成本效益和兼容性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/090d/11408894/ff1ac0d1bbcd/jmir_v26i1e60773_fig7.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/090d/11408894/84a7a585c631/jmir_v26i1e60773_fig1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/090d/11408894/013b3d691a9a/jmir_v26i1e60773_fig2.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/090d/11408894/44323305f6af/jmir_v26i1e60773_fig5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/090d/11408894/63df2b337046/jmir_v26i1e60773_fig6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/090d/11408894/ff1ac0d1bbcd/jmir_v26i1e60773_fig7.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/090d/11408894/84a7a585c631/jmir_v26i1e60773_fig1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/090d/11408894/013b3d691a9a/jmir_v26i1e60773_fig2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/090d/11408894/c2c353b4ad84/jmir_v26i1e60773_fig3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/090d/11408894/cc0e54d99319/jmir_v26i1e60773_fig4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/090d/11408894/44323305f6af/jmir_v26i1e60773_fig5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/090d/11408894/63df2b337046/jmir_v26i1e60773_fig6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/090d/11408894/ff1ac0d1bbcd/jmir_v26i1e60773_fig7.jpg

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