Department of Psychiatry, Beth Israel Deaconess Medical Center, Boston, Massachusetts.
JAMA Netw Open. 2022 Dec 1;5(12):e2248784. doi: 10.1001/jamanetworkopen.2022.48784.
IMPORTANCE: As more patients and clinicians are turning to mental health smartphone apps to expand access to services, little is known about the current state of the app marketplaces and what these apps are actually offering in terms of features, privacy, price, and services. OBJECTIVE: To assess the current state of mental health apps, explore the association between app privacy scores and popularity as measured by star ratings and downloads, and to understand opportunities and challenges facing the commercial app landscape. DESIGN, SETTING, AND PARTICIPANTS: This cross-sectional study had trained raters using the public-facing M-Health Index and Navigation Database (MIND) to assess and review 578 mental health apps. The sample of apps used in this analysis were pulled from MIND and include apps across various conditions including schizophrenia, eating disorders, sleep, and more. Analysis of these apps was conducted in June 2022. EXPOSURES: There were 578 mental health apps rated across 105 dimensions derived from the American Psychiatric Association's app evaluation framework. MAIN OUTCOMES AND MEASURES: App raters assessed each app across 6 categories: (1) app origin and accessibility, (2) privacy and security, (3) clinical foundation, (4) features and engagement, (5) inputs and outputs, and (6) interoperability. Privacy scores were determined by 5 MIND criteria, including (1) having a privacy policy, (2) reporting security measures in place, (3) declaring data use and purpose, (4) allowing for the deletion of data, and (5) allowing users to opt out of data collection. Correlations between privacy scores and popularity metrics (star ratings and number of downloads) were measured. RESULTS: This study included 578 mental health apps that were identified, assessed, and analyzed across 105 MIND dimensions. Psychoeducation, goal setting, and mindfulness were among the top app features. Of the 578 apps analyzed, 443 (77%) had a privacy policy. This analysis of apps with a privacy policy revealed that there was no statistically significant correlation between privacy scores and Apple App Store (r = 0.058, P = .29) or Google Play Store star ratings (r = 0.041; P = .48). The number of app downloads on the Google Play Store, however, was weakly correlated with privacy scores (χ25 = 22.1; P < .001). CONCLUSIONS AND RELEVANCE: In this cross-sectional study of mental health apps, findings indicate that the current app marketplaces primarily offered basic features such as psychoeducation, goal tracking, and mindfulness but fewer innovative features such as biofeedback or specialized therapies. Privacy challenges remained common, and app popularity metrics provided little help in identifying apps with more privacy.
重要性:随着越来越多的患者和临床医生转向心理健康智能手机应用程序来扩大服务的可及性,人们对应用程序市场的现状以及这些应用程序在功能、隐私、价格和服务方面提供的内容知之甚少。
目的:评估心理健康应用程序的现状,探索应用程序隐私评分与受欢迎程度之间的关联,受欢迎程度由星级评分和下载量来衡量,并了解商业应用程序领域面临的机遇和挑战。
设计、设置和参与者:本横断面研究使用面向公众的 M-Health Index 和导航数据库 (MIND) 对经过培训的评估人员进行培训,以评估和审查 578 个心理健康应用程序。本分析中使用的应用程序样本来自 MIND,包括各种条件下的应用程序,包括精神分裂症、饮食失调、睡眠等。该分析于 2022 年 6 月进行。
暴露:有 578 个心理健康应用程序在 105 个维度上进行了评分,这些维度源自美国精神病学协会的应用程序评估框架。
主要结果和措施:应用程序评估人员从以下 6 个类别评估每个应用程序:(1)应用程序来源和可访问性,(2)隐私和安全性,(3)临床基础,(4)功能和参与度,(5)输入和输出,以及 (6)互操作性。隐私评分由 MIND 的 5 个标准确定,包括 (1)具有隐私政策,(2)报告已采取的安全措施,(3)报告数据用途和目的,(4)允许删除数据,以及 (5)允许用户选择退出数据收集。测量了隐私评分与受欢迎程度指标(星级评分和下载量)之间的相关性。
结果:本研究共纳入 578 个心理健康应用程序,这些应用程序在 105 个 MIND 维度上进行了识别、评估和分析。心理健康教育、目标设定和正念是顶级应用功能。在分析的 578 个应用程序中,有 443 个(77%)有隐私政策。对有隐私政策的应用程序进行分析发现,隐私评分与苹果应用商店(r=0.058,P=0.29)或谷歌应用商店(r=0.041;P=0.48)的星级评分之间没有统计学上的显著相关性。然而,谷歌应用商店上的应用程序下载量与隐私评分呈弱相关(χ25=22.1;P<0.001)。
结论和相关性:在这项对心理健康应用程序的横断面研究中,研究结果表明,当前的应用程序市场主要提供基本功能,如心理健康教育、目标跟踪和正念,但较少提供创新功能,如生物反馈或专门的治疗方法。隐私挑战仍然很常见,应用程序受欢迎程度指标几乎无法帮助识别隐私保护更好的应用程序。
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