Accepted for/Published in: JMIR mHealth and uHealth
Date Submitted: Apr 2, 2020
Date Accepted: Nov 30, 2020
Examining the Correlation between Depression and Social Behavior on Smartphones through Usage Metadata: An Empirical Study
ABSTRACT
Background:
As smartphone has been widely used, understanding how depression correlates with social behavior on smartphones can be beneficial for early diagnosis of depression. An enormous amount of research relied on self-report questionnaires, which was not objective. Only recently, the increased availability of rich data about human behavior in digital space has provided new perspectives for the investigation of individual differences.
Objective:
The objective of this study was to explore depressed users' social behavior in digital space through metadata collected via smartphones.
Methods:
A total of 120 participants were recruited to carry a smartphone with a metadata collection application (MobileSens). At the end of metadata collection, they were instructed to complete the Center for Epidemiological Studies-Depression Scale (CES-D). We then separated participants into non-depressed and depressed groups based on their scores on CES-D. 44 features about social behavior were extracted from the metadata of smartphone usage. The two-way ANOVA analysis (non-depressed vs. depressed × male vs. female) and multiple logistic regression analysis were conducted to investigate differences in social behaviors on smartphones among users.
Results:
The results found depressed users received less calls from contacts (all day: F(1,116)=3.995, P=.048, η^2=.033; afternoon: F(1,116)=5.278, P=.02, η^2=.044), and used social applications more frequently (all day: F(1,116)=6.801, P=.01, η^2=.055; evening: F(1,116)=6.902, P=.01, η^2=.056) than non-depressed ones. In depressed group, females used Weibo more frequently than males (all day: F(1,116)=11.744, P=.001, η^2=.092; morning: F(1,116)=9.105, P=.003, η^2=.073; afternoon: F(1,116)=14.224, P<.001, η^2=.109; evening: F(1,116)=9.052, P=.003, η^2=.072). Moreover, usage of social applications in the evening emerged as a predictor of depressive symptoms for both all participants (OR=1.007, P=.02) and male (OR=1.013, P=.01), and usage of Weibo in the morning emerged as a predictor for female (OR=1.183, P=.03).
Conclusions:
This paper finds that there exists a certain correlation between depression and social behavior on smartphones. The result may be useful to improve social interaction for depressed individuals in the daily lives and may be insightful for early diagnosis of depression.
Citation
Request queued. Please wait while the file is being generated. It may take some time.
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.