谁在移动设备上追踪健康数据：香港的行为日志文件分析。

Who is Tracking Health on Mobile Devices: Behavioral Logfile Analysis in Hong Kong.

机构信息

Department of Media and Communication, City University of Hong Kong, Hong Kong, China (Hong Kong).

Department of Communication, Michigan State University, East Lansing, MI, United States.

出版信息

JMIR Mhealth Uhealth. 2019 May 23;7(5):e13679. doi: 10.2196/13679.

DOI:10.2196/13679

PMID:31120429

原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6552450/

Abstract

BACKGROUND

Health apps on mobile devices provide an unprecedented opportunity for ordinary people to develop social connections revolving around health issues. With increasing penetration of mobile devices and well-recorded behavioral data on such devices, it is desirable to employ digital traces on mobile devices rather than self-reported measures to capture the behavioral patterns underlying the use of mobile health (mHealth) apps in a more direct and valid way.

OBJECTIVE

The objectives of this study were to (1) assess the demographic predictors of the adoption of mHealth apps; (2) investigate the temporal pattern underlying the use of mHealth apps; and (3) explore the impacts of demographic variables, temporal features, and app genres on the use of mHealth apps.

METHODS

Logfile data of mobile devices were collected from a representative panel of about 2500 users in Hong Kong. Users' mHealth app activities were analyzed. We first conducted a binary logistic regression analysis to uncover demographic predictors of users' adoption status. Then we utilized a multilevel negative binomial regression to examine the impacts of demographic characteristics, temporal features, and app genres on mHealth app use.

RESULTS

It was found that 27.5% of mobile device users in Hong Kong adopt at least one genre of mHealth app. Adopters of mHealth apps tend to be female and better educated. However, demographic characteristics did not showcase the predictive powers on the use of mHealth apps, except for the gender effect (B vs B=-0.18; P=.006). The use of mHealth apps demonstrates a significant temporal pattern, which is found to be moderately active during daytime and intensifying at weekends and at night. Such temporal patterns in mHealth apps use are moderated by individuals' demographic characteristics. Finally, demographic characteristics were also found to condition the use of different genres of mHealth apps.

CONCLUSIONS

Our findings suggest the importance of dynamic perspective in understanding users' mHealth app activities. mHealth app developers should consider more the demographic differences in temporal patterns of mHealth apps in the development of mHealth apps. Furthermore, our research also contributes to the promotion of mHealth apps by emphasizing the differences of usage needs for various groups of users.

摘要

背景

移动设备上的健康应用程序为普通人围绕健康问题建立社交联系提供了前所未有的机会。随着移动设备的普及和此类设备上行为数据的良好记录，人们希望利用移动设备上的数字痕迹，而不是自我报告的措施，以更直接和有效的方式捕捉移动健康 (mHealth) 应用程序使用背后的行为模式。

目的

本研究的目的是：(1) 评估 mHealth 应用程序采用的人口统计学预测因素；(2) 研究 mHealth 应用程序使用的时间模式；(3) 探讨人口统计学变量、时间特征和应用程序类型对 mHealth 应用程序使用的影响。

方法

从香港约 2500 名代表性用户的样本中收集移动设备的日志数据。分析用户的 mHealth 应用程序活动。我们首先进行了二元逻辑回归分析，以揭示用户采用状态的人口统计学预测因素。然后，我们利用多层次负二项回归来检验人口统计学特征、时间特征和应用程序类型对 mHealth 应用程序使用的影响。

结果

发现在香港，27.5%的移动设备用户至少采用了一种 mHealth 应用程序类型。mHealth 应用程序的采用者往往是女性和受过更好教育的人。然而，人口统计学特征除了性别效应（B 与 B=-0.18；P=.006）外，并没有展示出对 mHealth 应用程序使用的预测能力。mHealth 应用程序的使用呈现出显著的时间模式，在白天活跃度较高，在周末和夜间活跃度增强。这种 mHealth 应用程序使用的时间模式受到个体人口统计学特征的调节。最后，人口统计学特征也被发现会影响不同类型的 mHealth 应用程序的使用。

结论

我们的研究结果表明，在理解用户的 mHealth 应用程序活动时，动态视角的重要性。mHealth 应用程序开发者在开发 mHealth 应用程序时，应更多地考虑 mHealth 应用程序时间模式的人口统计学差异。此外，我们的研究也通过强调不同用户群体的使用需求差异，为 mHealth 应用程序的推广做出了贡献。