AUTHOR=Tu Dongbo , Gao Xuliang , Wang Daxun , Cai Yan TITLE=A New Measurement of Internet Addiction Using Diagnostic Classification Models JOURNAL=Frontiers in Psychology VOLUME=8 YEAR=2017 URL=https://www.frontiersin.org/journals/psychology/articles/10.3389/fpsyg.2017.01768 DOI=10.3389/fpsyg.2017.01768 ISSN=1664-1078 ABSTRACT=

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.