Incorporation of Mobile Application (App) Measures into the Diagnosis of Smartphone Addiction

doi:10.4088/JCP.15m10310

機構典藏 > College of Engineering > Graduate Institute & Department of Electrical Engineering > Journal Article > Item 987654321/106362

Please use this identifier to cite or link to this item: https://tkuir.lib.tku.edu.tw/dspace/handle/987654321/106362

Title:	Incorporation of Mobile Application (App) Measures into the Diagnosis of Smartphone Addiction
Authors:	Lin, Yu-Hsuan;Lin, Po-Hsien;Chiang, Chih-Lin;Lee, Yang-Han;Yang, Cheryl C. H.;Kuo, Terry;Lin, Sheng-Hsuan
Date:	2017-07
Issue Date:	2016-04-22 13:47:28 (UTC+8)
Publisher:	Wiley-Blackwell Publishing Ltd.
Abstract:	OBJECTIVE:Global smartphone expansion has brought about unprecedented addictive behaviors. The current diagnosis of smartphone addiction is based solely on information from clinical interview. This study aimed to incorporate application (app)-recorded data into psychiatric criteria for the diagnosis of smartphone addiction and to examine the predictive ability of the app-recorded data for the diagnosis of smartphone addiction. METHODS: Smartphone use data of 79 college students were recorded by a newly developed app for 1 month between December 1, 2013, and May 31, 2014. For each participant, psychiatrists made a diagnosis for smartphone addiction based on 2 approaches: (1) only diagnostic interview (standard diagnosis) and (2) both diagnostic interview and app-recorded data (app-incorporated diagnosis). The app-incorporated diagnosis was further used to build app-incorporated diagnostic criteria. In addition, the app-recorded data were pooled as a score to predict smartphone addiction diagnosis. RESULTS: When app-incorporated diagnosis was used as a gold standard for 12 candidate criteria, 7 criteria showed significant accuracy (area under receiver operating characteristic curve [AUC] > 0.7) and were constructed as app-incorporated diagnostic criteria, which demonstrated remarkable accuracy (92.4%) for app-incorporated diagnosis. In addition, both frequency and duration of daily smartphone use significantly predicted app-incorporated diagnosis (AUC = 0.70 for frequency; AUC = 0.72 for duration). The combination of duration, frequency, and frequency trend for 1 month can accurately predict smartphone addiction diagnosis (AUC = 0.79 for app-incorporated diagnosis; AUC = 0.71 for standard diagnosis). CONCLUSIONS: The app-incorporated diagnosis, combining both psychiatric interview and app-recorded data, demonstrated substantial accuracy for smartphone addiction diagnosis. In addition, the app-recorded data performed as an accurate screening tool for app-incorporated diagnosis.
Relation:	Journal of Clinical Psychiatry 78(7), p.866-872
DOI:	10.4088/JCP.15m10310
Appears in Collections:	[Graduate Institute & Department of Electrical Engineering] Journal Article

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