Incorporation of mobile application (app) measures into the diagnosis of smartphone addiction

Yu Hsuan Lin, Po Hsien Lin, Chih Lin Chiang, Yang Han Lee, Cheryl C.H. Yang, Terry B.J. Kuo, Sheng Hsuan Lin

Research output: Contribution to journalArticle

8 Citations (Scopus)

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 (appincorporated 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.

Original languageEnglish
Pages (from-to)866-872
Number of pages7
JournalJournal of Clinical Psychiatry
Volume78
Issue number7
DOIs
Publication statusPublished - Jul 1 2017
Externally publishedYes

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Mobile Applications
Area Under Curve
Interviews
Smartphone
Psychiatry
Addictive Behavior
Aptitude

ASJC Scopus subject areas

  • Psychiatry and Mental health

Cite this

Incorporation of mobile application (app) measures into the diagnosis of smartphone addiction. / Lin, Yu Hsuan; Lin, Po Hsien; Chiang, Chih Lin; Lee, Yang Han; Yang, Cheryl C.H.; Kuo, Terry B.J.; Lin, Sheng Hsuan.

In: Journal of Clinical Psychiatry, Vol. 78, No. 7, 01.07.2017, p. 866-872.

Research output: Contribution to journalArticle

Lin, Yu Hsuan ; Lin, Po Hsien ; Chiang, Chih Lin ; Lee, Yang Han ; Yang, Cheryl C.H. ; Kuo, Terry B.J. ; Lin, Sheng Hsuan. / Incorporation of mobile application (app) measures into the diagnosis of smartphone addiction. In: Journal of Clinical Psychiatry. 2017 ; Vol. 78, No. 7. pp. 866-872.
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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 (appincorporated 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.",
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