Department of Psychiatry, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Boston, Massachusetts, USA.
Department of Biostatistics, Harvard TH Chan School of Public Health, Boston, Massachusetts, USA.
Evid Based Ment Health. 2019 Feb;22(1):4-9. doi: 10.1136/ebmental-2018-300069. Epub 2019 Jan 11.
This study aimed to understand the attributes of popular apps for mental health and comorbid medical conditions, and how these qualities relate to consumer ratings, app quality and classification by the WHO health app classification framework.
We selected the 10 apps from the Apple iTunes store and the US Android Google Play store on 20 July 2018 from six disease states: depression, anxiety, schizophrenia, addiction, diabetes and hypertension. Each app was downloaded by two authors who provided information on the apps' attributes, functionality, interventions, popularity, scientific backing and WHO app classification rating.
A total of 120 apps were examined. Although none of these apps had Food and Drug Administration marketing approval, nearly 50% made claims that appeared medical. Most apps offered a similar type of services with 87.5% assigned WHO classification 1.4.2 'self-monitoring of health or diagnostic data by a client' or 1.6.1 'client look-up of health information'. The 'last updated' attribute was highly correlated with a quality rating of the app although no apps features (eg, uses Global Positioning System, reminders and so on) were.
Due to the heterogeneity of the apps, we were unable to define a core set of features that would accurately assess app quality. The number of apps making unsupported claims combined with the number of apps offering questionable content warrants a cautious approach by both patients and clinicians in selecting safe and effective ones.
'Days since last updated' offers a useful and easy clinical screening test for health apps, regardless of the condition being examined.
本研究旨在了解针对心理健康和共病医学状况的热门应用程序的属性,以及这些质量与消费者评分、应用程序质量和世界卫生组织健康应用程序分类框架分类之间的关系。
我们于 2018 年 7 月 20 日从六个疾病状态(抑郁症、焦虑症、精神分裂症、成瘾、糖尿病和高血压)从苹果 iTunes 商店和美国 Android Google Play 商店中选择了前 10 名应用程序。两名作者下载了每个应用程序,并提供了有关应用程序属性、功能、干预措施、受欢迎程度、科学依据和世界卫生组织应用程序分类评分的信息。
共检查了 120 个应用程序。尽管这些应用程序均未获得食品和药物管理局的营销批准,但近 50%的应用程序声称具有医疗用途。大多数应用程序提供了类似的服务,其中 87.5%的应用程序被世界卫生组织分类为 1.4.2“由客户自行监测健康或诊断数据”或 1.6.1“客户查看健康信息”。“最后更新”属性与应用程序的质量评分高度相关,尽管没有应用程序功能(例如,使用全球定位系统,提醒等)。
由于应用程序的异质性,我们无法确定一组可准确评估应用程序质量的核心功能。许多应用程序都提出了未经证实的主张,同时也提供了一些可疑的内容,这使得患者和临床医生在选择安全有效的应用程序时都需要谨慎。
“自上次更新以来的天数”为健康应用程序提供了一种有用且简便的临床筛选测试,无论检查的疾病状态如何。