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[应用“半自动回顾性应用商店分析”方法识别苹果应用商店中的风湿病健康应用程序:一项纵向观察]

[Identification of rheumatological health apps in the Apple app store applying the "semiautomatic retrospective app store analysis" method : A longitudinal observation].

作者信息

Richter J G, Chehab G, Kiltz U, Becker A, von Jan U, Albrecht U-V, Schneider M, Specker C

机构信息

Poliklinik und Funktionsbereich Rheumatologie & Hiller-Forschungszentrum Rheumatologie, Medizinische Fakultät, Heinrich-Heine-Universität Düsseldorf, Universitätsklinikum Düsseldorf, Moorenstr. 5, 40225, Düsseldorf, Deutschland.

Rheumazentrum Ruhrgebiet, Ruhr-Universität Bochum, Herne, Deutschland.

出版信息

Z Rheumatol. 2021 Dec;80(10):943-952. doi: 10.1007/s00393-021-01099-9. Epub 2021 Oct 11.

Abstract

BACKGROUND

The Apple and Google app stores offer a wide range of health apps. It is still a challenge to find valuable and qualified apps.

OBJECTIVE

Can German language apps be identified using the "semiautomated retrospective app store analysis" (SARASA) method for the field of rheumatology?

MATERIAL AND METHOD

The SARASA is a semiautomated method to select and characterize apps listed in the app store. After the first application in February 2018 SARASA was applied again to the Apple app store in February 2020.

RESULTS

In February 2018 it was possible to acquire metadata for 103,046 apps and in February 2020 data for 94,735 apps that were listed in the category "health and fitness" or "medicine" in Apple's app store frontend for Germany. After applying the search terms 59 apps with a German language app description were identified for the field of rheumatology in 2018 and 53 apps in 2020. For these, more detailed manual reviews seem worthwhile. In 2018, the apps found were more likely to address patients than physicians and this was more balanced in 2020. In addition, it became apparent that for certain diseases there was no app developer activity. The percentage breakdown of matches by search term revealed substantial fluctuations in the app market when comparing 2018 to 2020.

DISCUSSION

The SARASA method provides a useful tool to identify apps from app stores that meet predefined, formal criteria. Subsequent manual checks of the quality of the contents are still necessary. Further development of the SARASA method and consensus and standardization of quality criteria are worthwhile. Quality criteria should be considered for offers of mobile health apps in app stores.

摘要

背景

苹果和谷歌应用商店提供了大量的健康应用程序。找到有价值且合格的应用程序仍然是一项挑战。

目的

能否使用“半自动回顾性应用商店分析”(SARASA)方法来识别风湿病领域的德语应用程序?

材料与方法

SARASA是一种用于选择和描述应用商店中列出的应用程序的半自动方法。在2018年2月首次应用后,SARASA于2020年2月再次应用于苹果应用商店。

结果

2018年2月,有可能获取103,046个应用程序的元数据,2020年2月,获取了苹果德国应用商店前端“健康与健身”或“医学”类别下列出的94,735个应用程序的数据。应用搜索词后,2018年在风湿病领域识别出59个带有德语应用描述的应用程序,2020年为53个。对于这些应用程序,进行更详细的人工审查似乎是值得的。2018年,找到的应用程序更倾向于面向患者而非医生,而在2020年这种情况更加平衡。此外,很明显对于某些疾病没有应用程序开发者活动。比较2018年和2020年,按搜索词匹配的百分比细分显示应用程序市场存在大幅波动。

讨论

SARASA方法提供了一个有用的工具,可从应用商店中识别符合预定义形式标准的应用程序。后续仍需对内容质量进行人工检查。SARASA方法的进一步开发以及质量标准的共识和标准化是值得的。应用商店中移动健康应用程序的提供应考虑质量标准。

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