A New Measurement of Internet Addiction Using Diagnostic Classification Models Article Swipe

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Dongbo Tu , Xuliang Gao , Daxun Wang , Yan Cai ·

YOU? · · 2017 · Open Access · · DOI: https://doi.org/10.3389/fpsyg.2017.01768

To obtain accurate, valid, and rich information from the questionnaires for internet addiction, a diagnostic classification test for internet addiction (the DCT-IA) was developed using diagnostic classification models (DCMs), a cutting-edge psychometric theory, based on DSM-5. A calibration sample and a validation sample were recruited in this study to calibrate the item parameters of the DCT-IA and to examine the sensitivity and specificity. The DCT-IA had high reliability and validity based on both CTT and DCMs, and had a sensitivity of 0.935 and a specificity of 0.817 with AUC = 0.919. More important, different from traditional questionnaires, the DCT-IA can simultaneously provide general-level diagnostic information and the detailed symptom criteria-level information about the posterior probability of satisfying each symptom criterion in DMS-5 for each patient, which gives insight into tailoring individual-specific treatments for internet addiction.

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Addiction Psychology The Internet Data science Psychiatry World Wide Web Computer science

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Type: article
Language: en
Landing Page: https://doi.org/10.3389/fpsyg.2017.01768
PDF: https://www.frontiersin.org/articles/10.3389/fpsyg.2017.01768/pdf
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Cited By: 20
References: 31
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DOI: https://doi.org/10.3389/fpsyg.2017.01768

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Title: A New Measurement of Internet Addiction Using Diagnostic Classification Models

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Language: en

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Publication year: 2017

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Publication date: 2017-10-10

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Authors: Dongbo Tu, Xuliang Gao, Daxun Wang, Yan Cai

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Landing page: https://doi.org/10.3389/fpsyg.2017.01768

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OA URL: https://www.frontiersin.org/articles/10.3389/fpsyg.2017.01768/pdf

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Concepts: Addiction, Psychology, The Internet, Data science, Psychiatry, World Wide Web, Computer science

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Cited by: 20

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abstract_inverted_index.addiction.	134
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