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https://tkuir.lib.tku.edu.tw/dspace/handle/987654321/106362
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题名: | Incorporation of Mobile Application (App) Measures into the Diagnosis of Smartphone Addiction |
作者: | Lin, Yu-Hsuan;Lin, Po-Hsien;Chiang, Chih-Lin;Lee, Yang-Han;Yang, Cheryl C. H.;Kuo, Terry;Lin, Sheng-Hsuan |
日期: | 2017-07 |
上传时间: | 2016-04-22 13:47:28 (UTC+8) |
出版者: | Wiley-Blackwell Publishing Ltd. |
摘要: | 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. |
關聯: | Journal of Clinical Psychiatry 78(7), p.866-872 |
DOI: | 10.4088/JCP.15m10310 |
显示于类别: | [電機工程學系暨研究所] 期刊論文
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