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...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2017-10-01
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| Series: | Frontiers in Psychology |
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| Online Access: | http://journal.frontiersin.org/article/10.3389/fpsyg.2017.01768/full |
| _version_ | 1811302925845135360 |
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| author | Dongbo Tu Xuliang Gao Daxun Wang Yan Cai |
| author_facet | Dongbo Tu Xuliang Gao Daxun Wang Yan Cai |
| author_sort | Dongbo Tu |
| collection | DOAJ |
| 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. |
| first_indexed | 2024-04-13T07:38:02Z |
| format | Article |
| id | doaj.art-854db5ce63ea476bbfca29d169f82c13 |
| institution | Directory Open Access Journal |
| issn | 1664-1078 |
| language | English |
| last_indexed | 2024-04-13T07:38:02Z |
| publishDate | 2017-10-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Psychology |
| spelling | doaj.art-854db5ce63ea476bbfca29d169f82c132022-12-22T02:56:01ZengFrontiers Media S.A.Frontiers in Psychology1664-10782017-10-01810.3389/fpsyg.2017.01768302329A New Measurement of Internet Addiction Using Diagnostic Classification ModelsDongbo TuXuliang GaoDaxun WangYan CaiTo 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.http://journal.frontiersin.org/article/10.3389/fpsyg.2017.01768/fullmeasurementdiagnostic classification modelsinternet addictionsymptom criteria-level informationcognitive diagnosis models |
| spellingShingle | Dongbo Tu Xuliang Gao Daxun Wang Yan Cai A New Measurement of Internet Addiction Using Diagnostic Classification Models Frontiers in Psychology measurement diagnostic classification models internet addiction symptom criteria-level information cognitive diagnosis models |
| title | A New Measurement of Internet Addiction Using Diagnostic Classification Models |
| title_full | A New Measurement of Internet Addiction Using Diagnostic Classification Models |
| title_fullStr | A New Measurement of Internet Addiction Using Diagnostic Classification Models |
| title_full_unstemmed | A New Measurement of Internet Addiction Using Diagnostic Classification Models |
| title_short | A New Measurement of Internet Addiction Using Diagnostic Classification Models |
| title_sort | new measurement of internet addiction using diagnostic classification models |
| topic | measurement diagnostic classification models internet addiction symptom criteria-level information cognitive diagnosis models |
| url | http://journal.frontiersin.org/article/10.3389/fpsyg.2017.01768/full |
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