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从高血压管理移动健康应用中挖掘用户评论,探索影响用户满意度的因素及其非对称性:比较研究。

Mining User Reviews From Hypertension Management Mobile Health Apps to Explore Factors Influencing User Satisfaction and Their Asymmetry: Comparative Study.

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

JMIR Mhealth Uhealth. 2024 Mar 28;12:e55199. doi: 10.2196/55199.

DOI:10.2196/55199
PMID:38547475
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11009850/
Abstract

BACKGROUND

Hypertension significantly impacts the well-being and health of individuals globally. Hypertension management apps (HMAs) have been shown to assist patients in controlling blood pressure (BP), with their efficacy validated in clinical trials. However, the utilization of HMAs continues to be suboptimal. Presently, there is a dearth of real-world research based on big data and exploratory mining that compares Chinese and American HMAs.

OBJECTIVE

This study aims to systematically gather HMAs and their user reviews from both China and the United States. Subsequently, using data mining techniques, the study aims to compare the user experience, satisfaction levels, influencing factors, and asymmetry between Chinese and American users of HMAs. In addition, the study seeks to assess the disparities in satisfaction and its determinants while delving into the asymmetry of these factors.

METHODS

The study sourced HMAs and user reviews from 10 prominent Chinese and American app stores globally. Using the latent Dirichlet allocation (LDA) topic model, the research identified various topics within user reviews. Subsequently, the Tobit model was used to investigate the impact and distinctions of each topic on user satisfaction. The Wald test was applied to analyze differences in effects across various factors.

RESULTS

We examined a total of 261 HMAs along with their associated user reviews, amounting to 116,686 reviews in total. In terms of quantity and overall satisfaction levels, Chinese HMAs (n=91) and corresponding reviews (n=16,561) were notably fewer compared with their American counterparts (n=220 HMAs and n=100,125 reviews). The overall satisfaction rate among HMA users was 75.22% (87,773/116,686), with Chinese HMAs demonstrating a higher satisfaction rate (13,866/16,561, 83.73%) compared with that for American HMAs (73,907/100,125, 73.81%). Chinese users primarily focus on reliability (2165/16,561, 13.07%) and measurement accuracy (2091/16,561, 12.63%) when considering HMAs, whereas American users prioritize BP tracking (17,285/100,125, 17.26%) and data synchronization (12,837/100,125, 12.82%). Seven factors (easy to use: P<.001; measurement accuracy: P<.001; compatibility: P<.001; cost: P<.001; heart rate detection function: P=.02; blood pressure tracking function: P<.001; and interface design: P=.01) significantly influenced the positive deviation (PD) of Chinese HMA user satisfaction, while 8 factors (easy to use: P<.001; reliability: P<.001; measurement accuracy: P<.001; compatibility: P<.001; cost: P<.001; interface design: P<.001; real-time: P<.001; and data privacy: P=.001) affected the negative deviation (ND). Notably, BP tracking had the greatest effect on PD (β=.354, P<.001), while cost had the most significant impact on ND (β=3.703, P<.001). All 12 factors (easy to use: P<.001; blood pressure tracking function: P<.001; data synchronization: P<.001; blood pressure management effect: P<.001; heart rate detection function: P<.001; data sharing: P<.001; reliability: P<.001; compatibility: P<.001; interface design: P<.001; advertisement distribution: P<.001; measurement accuracy: P<.001; and cost: P<.001) significantly influenced the PD and ND of American HMA user satisfaction. Notably, BP tracking had the greatest effect on PD (β=0.312, P<.001), while data synchronization had the most significant impact on ND (β=2.662, P<.001). In addition, the influencing factors of PD and ND in user satisfaction of HMA in China and the United States are different.

CONCLUSIONS

User satisfaction factors varied significantly between different countries, showing considerable asymmetry. For Chinese HMA users, ease of use and interface design emerged as motivational factors, while factors such as cost, measurement accuracy, and compatibility primarily contributed to user dissatisfaction. For American HMA users, motivational factors were ease of use, BP tracking, BP management effect, interface design, measurement accuracy, and cost. Moreover, users expect features such as data sharing, synchronization, software reliability, compatibility, heart rate detection, and nonintrusive advertisement distribution. Tailored experience plans should be devised for different user groups in various countries to address these diverse preferences and requirements.

摘要

背景

高血压显著影响全球个体的健康和福祉。高血压管理应用程序(HMAs)已被证明有助于患者控制血压,其在临床试验中的有效性已得到验证。然而,HMAs 的使用仍然不理想。目前,基于大数据和探索性挖掘的真实世界研究缺乏比较中、美 HMA 的研究。

目的

本研究旨在系统地收集中、美两国的 HMA 及其用户评论,并使用数据挖掘技术比较中美 HMA 用户的用户体验、满意度水平、影响因素和不对称性。此外,还评估了满意度差异及其决定因素,并深入探讨了这些因素的不对称性。

方法

本研究从全球 10 个知名的中、美应用商店中获取 HMA 和用户评论。使用潜在狄利克雷分配(LDA)主题模型,研究人员在用户评论中识别出了各种主题。随后,采用 Tobit 模型研究每个主题对用户满意度的影响和差异。采用 Wald 检验分析了不同因素的影响差异。

结果

我们共研究了 261 个 HMA 及其相关的用户评论,总计 116686 条评论。就数量和整体满意度水平而言,中国的 HMA(n=91)及其对应的评论(n=16561)明显少于美国的 HMA(n=220 和 n=100125)。HMA 用户的整体满意度率为 75.22%(87773/116686),其中中国 HMA 的满意度率(13866/16561,83.73%)高于美国 HMA(73907/100125,73.81%)。中国用户在考虑 HMA 时主要关注可靠性(2165/16561,13.07%)和测量精度(2091/16561,12.63%),而美国用户则更注重血压跟踪(17285/100125,17.26%)和数据同步(12837/100125,12.82%)。七个因素(易用性:P<.001;测量精度:P<.001;兼容性:P<.001;成本:P<.001;心率检测功能:P=.02;血压跟踪功能:P<.001;界面设计:P=.01)显著影响中国 HMA 用户满意度的正偏差(PD),而 8 个因素(易用性:P<.001;可靠性:P<.001;测量精度:P<.001;兼容性:P<.001;成本:P<.001;界面设计:P<.001;实时性:P<.001;数据隐私:P=.001)影响负偏差(ND)。值得注意的是,血压跟踪对 PD 的影响最大(β=.354,P<.001),而成本对 ND 的影响最大(β=3.703,P<.001)。所有 12 个因素(易用性:P<.001;血压跟踪功能:P<.001;数据同步:P<.001;血压管理效果:P<.001;心率检测功能:P<.001;数据共享:P<.001;可靠性:P<.001;兼容性:P<.001;界面设计:P<.001;广告分发:P<.001;测量精度:P<.001;和成本:P<.001)显著影响美国 HMA 用户满意度的 PD 和 ND。值得注意的是,血压跟踪对 PD 的影响最大(β=0.312,P<.001),而数据同步对 ND 的影响最大(β=2.662,P<.001)。此外,中、美 HMA 用户满意度的 PD 和 ND 的影响因素不同。

结论

不同国家的用户满意度因素存在显著差异,表现出较大的不对称性。对于中国 HMA 用户,易用性和界面设计是激励因素,而成本、测量精度和兼容性等因素主要导致用户不满。对于美国 HMA 用户,激励因素是易用性、血压跟踪、血压管理效果、界面设计、测量精度和成本。此外,用户还期望具有数据共享、同步、软件可靠性、兼容性、心率检测和非侵入性广告分发等功能。应针对不同国家的不同用户群体制定定制化的体验计划,以满足这些不同的偏好和需求。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/214f/11009850/146d983c82fe/mhealth_v12i1e55199_fig2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/214f/11009850/ae9d5dc9dde6/mhealth_v12i1e55199_fig1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/214f/11009850/146d983c82fe/mhealth_v12i1e55199_fig2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/214f/11009850/ae9d5dc9dde6/mhealth_v12i1e55199_fig1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/214f/11009850/146d983c82fe/mhealth_v12i1e55199_fig2.jpg

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本文引用的文献

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2
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Front Public Health. 2023 Mar 1;11:1049396. doi: 10.3389/fpubh.2023.1049396. eCollection 2023.
3
Encouraging brisk walking with the free Active10 app in postnatal women who had a hypertensive pregnancy: "Just Walk It" feasibility study.
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4
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PLoS One. 2025 Mar 19;20(3):e0319828. doi: 10.1371/journal.pone.0319828. eCollection 2025.
5
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4
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