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J Psychiatr Res. 2015 Jun;65:139-45. doi: 10.1016/j.jpsychires.2015.04.003. Epub 2015 Apr 10.

Time distortion associated with smartphone addiction: Identifying smartphone addiction via a mobile application (App).

Author information

1
Institute of Brain Science, National Yang-Ming University, Taipei, Taiwan; Sleep Research Center, National Yang-Ming University, Taipei, Taiwan.
2
Department and Graduate School of Electrical Engineering, Tamkang University Hospital, New Taipei City, Taiwan.
3
Department of Psychiatry, Koo Foundation Sun Yat-Sen Cancer Center, New Taipei City, Taiwan.
4
Department of Epidemiology, Harvard School of Public Health, Boston, MA, USA.
5
Department of Psychiatry, National Taiwan University, College of Medicine, Taipei, Taiwan.
6
Department and Graduate School of Electrical Engineering, Tamkang University Hospital, New Taipei City, Taiwan; Department of Computer and Communication Engineering, De-Lin Institution of Technology, New Taipei City, Taiwan.
7
Institute of Brain Science, National Yang-Ming University, Taipei, Taiwan; Sleep Research Center, National Yang-Ming University, Taipei, Taiwan; Brain Research Center, National Yang-Ming University, Taipei, Taiwan.
8
Institute of Brain Science, National Yang-Ming University, Taipei, Taiwan; Sleep Research Center, National Yang-Ming University, Taipei, Taiwan; Brain Research Center, National Yang-Ming University, Taipei, Taiwan; Institute of Translational and Interdisciplinary Medicine, National Central University, Taoyuan, Taiwan. Electronic address: cchyang@ym.edu.tw.

Abstract

BACKGROUND:

Global smartphone penetration has brought about unprecedented addictive behaviors.

AIMS:

We report a proposed diagnostic criteria and the designing of a mobile application (App) to identify smartphone addiction.

METHOD:

We used a novel empirical mode decomposition (EMD) to delineate the trend in smartphone use over one month.

RESULTS:

The daily use count and the trend of this frequency are associated with smartphone addiction. We quantify excessive use by daily use duration and frequency, as well as the relationship between the tolerance symptoms and the trend for the median duration of a use epoch. The psychiatrists' assisted self-reporting use time is significant lower than and the recorded total smartphone use time via the App and the degree of underestimation was positively correlated with actual smartphone use.

CONCLUSIONS:

Our study suggests the identification of smartphone addiction by diagnostic interview and via the App-generated parameters with EMD analysis.

KEYWORDS:

Empirical mode decomposition; Internet addiction; Mobile application; Smartphone addiction

[Indexed for MEDLINE]

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