English  |  正體中文  |  简体中文  |  Items with full text/Total items : 62797/95867 (66%)
Visitors : 3741324      Online Users : 516
RC Version 7.0 © Powered By DSPACE, MIT. Enhanced by NTU Library & TKU Library IR team.
Scope Tips:
  • please add "double quotation mark" for query phrases to get precise results
  • please goto advance search for comprehansive author search
  • Adv. Search
    HomeLoginUploadHelpAboutAdminister Goto mobile version
    Please use this identifier to cite or link to this item: https://tkuir.lib.tku.edu.tw/dspace/handle/987654321/106177


    Title: Time Distortion Associated with Smartphone Addiction: Identifying Smartphone Addiction via a Mobile Application (App)
    Authors: Lin, Yu-Hsuan;Lin, Yu-Cheng;Lee,Yang-Han;Lin,Po-Hsien;Lin, Sheng-Hsuan;Chang, Li-Ren;Tseng,Hsien-Wei;Yen,Liang-Yu;Yang, Cheryl C.H.;Kuo, Terry B.J.
    Keywords: Smartphone addiction;Internet addiction;Mobile application;Empirical mode decomposition
    Date: 2015-06
    Issue Date: 2016-04-22 13:23:08 (UTC+8)
    Publisher: Pergamon Press
    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.
    Relation: Journal of Psychiatric Research 65, p.139-145
    DOI: 10.1016/j.jpsychires.2015.04.003
    Appears in Collections:[Graduate Institute & Department of Electrical Engineering] Journal Article

    Files in This Item:

    File Description SizeFormat
    index.html0KbHTML223View/Open

    All items in 機構典藏 are protected by copyright, with all rights reserved.


    DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library & TKU Library IR teams. Copyright ©   - Feedback