Accepted for/Published in: JMIR mHealth and uHealth
Date Submitted: Feb 11, 2019
Open Peer Review Period: Feb 12, 2019 - Feb 20, 2019
Date Accepted: Apr 29, 2019
Date Submitted to PubMed: May 24, 2019
(closed for review but you can still tweet)
Who is tracking health on mobile devices: A Behavioral Logfile Analysis in Hong Kong
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 apps in a more direct and valid way.
Objective:
The objectives of our study were to (1) assess the demographic predictors of the adoption of mobile health apps; (2) investigate the temporal pattern underlying the use of mobile health apps; (3) explore the impacts of demographic variables, temporal features, and app types on the use of mobile health apps.
Methods:
Log data of mobile devices was collected from a representative panel of about 2,500 users in Hong Kong. Users’ health app activities records were analyzed. We firstly conducted a binary logistic model to assess demographics predictors of user’s adoption status. Then we utilized a multi-level negative binomial regression to examine the impact of temporal pattern, app type, and user’s demographic characteristics on health app usage time.
Results:
It is found that 27.5% of mobile device users in Hong Kong adopt at least one type of health apps. Adopters of mobile health apps tend to be female and better educated. However, demographic characteristics do not showcase the predictive powers on the use of mobile health apps, except for the gender effect (B female vs male= -0.18, SE = 0.066, p<0.01). The use of mobile health apps demonstrates a significant temporal pattern, which is found to be moderately active during daytime and intensifying at weekends and night. Such temporal patterns in mobile health apps use are moderated by individuals’ demographic characteristics.
Conclusions:
Our findings suggest the importance of temporal patterns in understanding user’s mobile health app activities. Mobile health app developers should consider more about the demographic differences in temporal patterns when they develop the apps. Besides, our research also contribute to the promotion of mobile health apps by emphasizing the differences of usage needs for various groups of people.
Citation
Per the author's request the PDF is not available.
Copyright
© The authors. All rights reserved. This is a privileged document currently under peer-review/community review (or an accepted/rejected manuscript). Authors have provided JMIR Publications with an exclusive license to publish this preprint on it's website for review and ahead-of-print citation purposes only. While the final peer-reviewed paper may be licensed under a cc-by license on publication, at this stage authors and publisher expressively prohibit redistribution of this draft paper other than for review purposes.