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JOURNAL ARTICLE
RESEARCH SUPPORT, NON-U.S. GOV'T
Time distortion associated with smartphone addiction: Identifying smartphone addiction via a mobile application (App).
Journal of Psychiatric Research 2015 June
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.
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.
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