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用于心血管风险评估的移动应用程序的综述与比较评估:使用移动健康应用程序可用性问卷进行的可用性评估

Review and Comparative Evaluation of Mobile Apps for Cardiovascular Risk Estimation: Usability Evaluation Using mHealth App Usability Questionnaire.

作者信息

Svenšek Adrijana, Gosak Lucija, Lorber Mateja, Štiglic Gregor, Fijačko Nino

机构信息

Faculty of Health Sciences, University of Maribor, Žitna ulica 15, Maribor, 2000, Slovenia, 386 2 300 4762.

Faculty of Electrical Engineering and Computer Science, University of Maribor, Maribor, Slovenia.

出版信息

JMIR Mhealth Uhealth. 2025 May 8;13:e56466. doi: 10.2196/56466.

Abstract

BACKGROUND

Cardiovascular diseases (CVD) are the leading cause of death and disability worldwide, and their prevention is a major public health priority. Detecting health issues early and assessing risk levels can significantly improve the chances of reducing mortality. Mobile apps can help estimate and manage CVD risks by providing users with personalized feedback, education, and motivation. Incorporating visual analysis into apps is an effective method for educating society. However, the usability evaluation and inclusion of visualization of these apps are often unclear and variable.

OBJECTIVE

The primary objective of this study is to review and compare the usability of existing apps designed to estimate CVD risk using the mHealth App Usability Questionnaire (MAUQ). This is not a traditional usability study involving user interaction design, but rather an assessment of how effectively these applications meet usability standards as defined by the MAUQ.

METHODS

First, we used predefined criteria to review 16 out of 2238 apps to estimate CVD risk in the Google Play Store and the Apple App Store. Based on the apps' characteristics (ie, developed for health care professionals or patient use) and their functions (single or multiple CVD risk calculators), we conducted a descriptive analysis. Then we also compared the usability of existing apps using the MAUQ and calculated the agreement among 3 expert raters.

RESULTS

Most apps used the Framingham Risk Score (8/16, 50%) and Atherosclerotic Cardiovascular Disease Risk (7/16, 44%) prognostic models to estimate CVD risk. The app with the highest overall MAUQ score was the MDCalc Medical Calculator (mean 6.76, SD 0.25), and the lowest overall MAUQ score was obtained for the CardioRisk Calculator (mean 3.96, SD 0.21). The app with the highest overall MAUQ score in the "ease-of-use" domain was the MDCalc Medical Calculator (mean 7, SD 0); in the domain "interface and satisfaction," it was the MDCalc Medical Calculator (mean 6.67, SD 0.33); and in the domain "usefulness," it was the ASCVD Risk Estimator Plus (mean 6.80, SD 0.32).

CONCLUSIONS

We found that the Framingham Risk Score is the most widely used prognostic model in apps for estimating CVD risk. The "ease-of-use" domain received the highest ratings. While more than half of the apps were suitable for both health care professionals and patients, only a few offered sophisticated visualizations for assessing CVD risk. Less than a quarter of the apps included visualizations, and those that did were single calculators. Our analysis of apps showed that they are an appropriate tool for estimating CVD risk.

摘要

背景

心血管疾病(CVD)是全球死亡和残疾的主要原因,其预防是公共卫生的首要任务。早期发现健康问题并评估风险水平可显著提高降低死亡率的几率。移动应用程序可以通过为用户提供个性化反馈、教育和激励来帮助估计和管理心血管疾病风险。将视觉分析融入应用程序是教育公众的有效方法。然而,这些应用程序的可用性评估以及可视化的纳入情况往往不明确且各不相同。

目的

本研究的主要目的是使用移动健康应用程序可用性问卷(MAUQ)来审查和比较现有用于估计心血管疾病风险的应用程序的可用性。这不是一项涉及用户交互设计的传统可用性研究,而是对这些应用程序在多大程度上有效满足MAUQ所定义的可用性标准的评估。

方法

首先,我们使用预定义标准对谷歌应用商店和苹果应用商店中2238个用于估计心血管疾病风险的应用程序中的16个进行审查。基于应用程序的特征(即针对医疗保健专业人员或患者使用而开发)及其功能(单一或多个心血管疾病风险计算器),我们进行了描述性分析。然后,我们还使用MAUQ比较了现有应用程序的可用性,并计算了3位专家评分者之间的一致性。

结果

大多数应用程序使用弗雷明汉风险评分(8/16,50%)和动脉粥样硬化性心血管疾病风险(7/16,44%)预后模型来估计心血管疾病风险。MAUQ总分最高的应用程序是MDCalc医学计算器(平均6.76,标准差0.25),而CardioRisk计算器的MAUQ总分最低(平均3.96,标准差0.21)。在“易用性”领域MAUQ总分最高的应用程序是MDCalc医学计算器(平均7,标准差0);在“界面与满意度”领域,是MDCalc医学计算器(平均6.67,标准差0.33);在“有用性”领域,是动脉粥样硬化性心血管疾病风险估计器升级版(平均6.80,标准差0.32)。

结论

我们发现弗雷明汉风险评分是应用程序中用于估计心血管疾病风险最广泛使用的预后模型。“易用性”领域获得的评分最高。虽然超过一半的应用程序适合医疗保健专业人员和患者使用,但只有少数应用程序提供用于评估心血管疾病风险的复杂可视化。不到四分之一的应用程序包含可视化内容,而且那些包含可视化的应用程序是单一计算器。我们对应用程序的分析表明,它们是估计心血管疾病风险的合适工具。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7662/12080973/f4b0f78d67d4/mhealth-v13-e56466-g001.jpg

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