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Development of a Computerized Adaptive Testing for Internet Addiction
Internet addiction disorder has become one of the most popular forms of addiction in psychological and behavioral areas, and measuring it is growing increasingly important in practice. This study aimed to develop a computerized adaptive testing to measure and assess internet addiction (CAT-IA) effic...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6514228/ https://www.ncbi.nlm.nih.gov/pubmed/31133939 http://dx.doi.org/10.3389/fpsyg.2019.01010 |
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author | Zhang, Yong Wang, Daxun Gao, Xuliang Cai, Yan Tu, Dongbo |
author_facet | Zhang, Yong Wang, Daxun Gao, Xuliang Cai, Yan Tu, Dongbo |
author_sort | Zhang, Yong |
collection | PubMed |
description | Internet addiction disorder has become one of the most popular forms of addiction in psychological and behavioral areas, and measuring it is growing increasingly important in practice. This study aimed to develop a computerized adaptive testing to measure and assess internet addiction (CAT-IA) efficiently. Four standardized scales were used to build the original item bank. A total of 59 polytomously scored items were finally chosen after excluding 42 items for failing the psychometric evaluation. For the final 59-item bank of CAT-IA, two simulation studies were conducted to investigate the psychometric properties, efficiency, reliability, concurrent validity, and predictive validity of CAT-IA under different stopping rules. The results showed that (1) the final 59 items met IRT assumptions, had high discrimination, showed good item-model fit, and were without DIF; and (2) the CAT-IA not only had high measurement accuracy in psychometric properties but also sufficient efficiency, reliability, concurrent validity, and predictive validity. The impact and limitations of CAT-IA were discussed, and several suggestions for future research were provided. |
format | Online Article Text |
id | pubmed-6514228 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-65142282019-05-27 Development of a Computerized Adaptive Testing for Internet Addiction Zhang, Yong Wang, Daxun Gao, Xuliang Cai, Yan Tu, Dongbo Front Psychol Psychology Internet addiction disorder has become one of the most popular forms of addiction in psychological and behavioral areas, and measuring it is growing increasingly important in practice. This study aimed to develop a computerized adaptive testing to measure and assess internet addiction (CAT-IA) efficiently. Four standardized scales were used to build the original item bank. A total of 59 polytomously scored items were finally chosen after excluding 42 items for failing the psychometric evaluation. For the final 59-item bank of CAT-IA, two simulation studies were conducted to investigate the psychometric properties, efficiency, reliability, concurrent validity, and predictive validity of CAT-IA under different stopping rules. The results showed that (1) the final 59 items met IRT assumptions, had high discrimination, showed good item-model fit, and were without DIF; and (2) the CAT-IA not only had high measurement accuracy in psychometric properties but also sufficient efficiency, reliability, concurrent validity, and predictive validity. The impact and limitations of CAT-IA were discussed, and several suggestions for future research were provided. Frontiers Media S.A. 2019-05-07 /pmc/articles/PMC6514228/ /pubmed/31133939 http://dx.doi.org/10.3389/fpsyg.2019.01010 Text en Copyright © 2019 Zhang, Wang, Gao, Cai and Tu. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Psychology Zhang, Yong Wang, Daxun Gao, Xuliang Cai, Yan Tu, Dongbo Development of a Computerized Adaptive Testing for Internet Addiction |
title | Development of a Computerized Adaptive Testing for Internet Addiction |
title_full | Development of a Computerized Adaptive Testing for Internet Addiction |
title_fullStr | Development of a Computerized Adaptive Testing for Internet Addiction |
title_full_unstemmed | Development of a Computerized Adaptive Testing for Internet Addiction |
title_short | Development of a Computerized Adaptive Testing for Internet Addiction |
title_sort | development of a computerized adaptive testing for internet addiction |
topic | Psychology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6514228/ https://www.ncbi.nlm.nih.gov/pubmed/31133939 http://dx.doi.org/10.3389/fpsyg.2019.01010 |
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