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A New Measurement of Internet Addiction Using Diagnostic Classification Models.

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 a... Full description

Journal Title: Frontiers in psychology 2017, Vol.8, p.1768
Main Author: Tu, Dongbo
Other Authors: Gao, Xuliang , Wang, Daxun , Cai, Yan
Format: Electronic Article Electronic Article
Language: English
Subjects:
ID: ISSN: 1664-1078 ; DOI: 10.3389/fpsyg.2017.01768
Link: http://search.proquest.com/docview/1955600864/?pq-origsite=primo
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title: A New Measurement of Internet Addiction Using Diagnostic Classification Models.
format: Article
creator:
  • Tu, Dongbo
  • Gao, Xuliang
  • Wang, Daxun
  • Cai, Yan
subjects:
  • Cognitive Diagnosis Models
  • Diagnostic Classification Models
  • Internet Addiction
  • Measurement
  • Symptom Criteria-Level Information
ispartof: Frontiers in psychology, 2017, Vol.8, p.1768
description: 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.
language: eng
source:
identifier: ISSN: 1664-1078 ; DOI: 10.3389/fpsyg.2017.01768
fulltext: fulltext
issn:
  • 16641078
  • 1664-1078
url: Link


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descriptionTo 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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