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移动医疗的理论进展:移动应用程序的系统评价

Theoretical Advancements in mHealth: A Systematic Review of Mobile Apps.

机构信息

a Wee Kim Wee School of Communication and Information , Nanyang Technological University , Singapore.

出版信息

J Health Commun. 2018;23(10-11):909-955. doi: 10.1080/10810730.2018.1544676. Epub 2018 Nov 19.

DOI:10.1080/10810730.2018.1544676
PMID:30449261
Abstract

There are now few hundred thousand healthcare apps, yet there is a gap in our understanding of the theoretical mechanisms for which, and how, technological features translate into improved healthcare outcomes. In particular, the technological convergence, within mobile health (mHealth) apps, of the processes of mass and interpersonal communication, and human-computer interaction requires greater parsing in the literature. This paper analyzed 85 empirical studies on mHealth apps using the Input-Mechanism-Output model. We found in the literature that, firstly, there is a greater emphasis on technological inputs (87%) of accessibility, usability, usage, and data quality, than health outputs (52%) such as system process efficiencies and individual level behavioral or health outcomes. Secondly, there is little evidence of explanatory mechanisms (19%) of how the effects of mHealth apps are achieved. While we believe that successful apps would require research that incorporates technological inputs, theoretical mechanisms and health outputs, such studies are a rarity (n = 3). There is a minor increase in rigor with randomized control trials (n = 5), and a preponderance of discussion around social influence (n = 8) and gamification (n = 7), albeit in a scattered manner. We discuss the implications of the trend towards socialization and gamification findings in terms of future research, particularly in terms of study design guided by theoretical mechanisms.

摘要

现在有数十万款医疗保健应用程序,但我们对于技术特性如何转化为改善医疗效果的理论机制还存在理解上的差距。特别是,移动健康(mHealth)应用程序中大众传播和人际传播过程以及人机交互的技术融合,在文献中需要更深入的解析。本文使用输入-机制-输出模型分析了 85 项关于 mHealth 应用程序的实证研究。我们在文献中发现,首先,与系统流程效率和个人层面的行为或健康结果等健康产出(52%)相比,人们更加关注可及性、可用性、使用情况和数据质量等技术投入(87%)。其次,关于 mHealth 应用程序如何实现其效果的解释机制(19%)的证据很少。虽然我们认为成功的应用程序需要将技术投入、理论机制和健康产出结合起来进行研究,但这样的研究很少见(n=3)。随机对照试验(n=5)的严谨性略有提高,而围绕社会影响(n=8)和游戏化(n=7)的讨论居多,尽管方式较为分散。我们讨论了社交化和游戏化发现的趋势对未来研究的影响,特别是在基于理论机制的研究设计方面。

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