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The Gambling Disorders Identification Test (GDIT): Psychometric Evaluation of a New Comprehensive Measure for Gambling Disorder and Problem Gambling
The novel gambling disorder identification test (GDIT) was recently developed in an international Delphi and consensus process. In this first psychometric evaluation, gamblers (N = 603) were recruited from treatment- and support-seeking contexts (n = 79 and n = 185), self-help groups (n = 47), and a...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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SAGE Publications
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9684656/ https://www.ncbi.nlm.nih.gov/pubmed/34617456 http://dx.doi.org/10.1177/10731911211046045 |
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author | Molander, Olof Wennberg, Peter Berman, Anne H |
author_facet | Molander, Olof Wennberg, Peter Berman, Anne H |
author_sort | Molander, Olof |
collection | PubMed |
description | The novel gambling disorder identification test (GDIT) was recently developed in an international Delphi and consensus process. In this first psychometric evaluation, gamblers (N = 603) were recruited from treatment- and support-seeking contexts (n = 79 and n = 185), self-help groups (n = 47), and a population sample (n = 292). Participants completed self-report measures, a GDIT retest (n = 499), as well as diagnostic semistructured interviews assessing gambling disorder (GD; n = 203). The GDIT showed excellent internal consistency reliability (α = .94) and test–retest reliability (6-16 days, intraclass correlation coefficient = 0.93). Confirmatory factor analysis yielded factor loadings supporting the three proposed GDIT domains of gambling behavior, gambling symptoms, and negative consequences. Receiver operator curves and clinical significance indicators were used to estimate GDIT cut-off scores in relation to recreational (<15) and problem gambling (15-19), any GD (≥20), mild GD (20-24), moderate GD (25-29), and severe GD (≥30). The GDIT can be considered a valid and reliable measure to identify and predict GD severity, as well as problem gambling. In addition, the GDIT improves content validity in relation to an international research agreement concerning features of gambling outcome measures, known as the Banff Consensus Agreement. |
format | Online Article Text |
id | pubmed-9684656 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | SAGE Publications |
record_format | MEDLINE/PubMed |
spelling | pubmed-96846562022-11-25 The Gambling Disorders Identification Test (GDIT): Psychometric Evaluation of a New Comprehensive Measure for Gambling Disorder and Problem Gambling Molander, Olof Wennberg, Peter Berman, Anne H Assessment Articles The novel gambling disorder identification test (GDIT) was recently developed in an international Delphi and consensus process. In this first psychometric evaluation, gamblers (N = 603) were recruited from treatment- and support-seeking contexts (n = 79 and n = 185), self-help groups (n = 47), and a population sample (n = 292). Participants completed self-report measures, a GDIT retest (n = 499), as well as diagnostic semistructured interviews assessing gambling disorder (GD; n = 203). The GDIT showed excellent internal consistency reliability (α = .94) and test–retest reliability (6-16 days, intraclass correlation coefficient = 0.93). Confirmatory factor analysis yielded factor loadings supporting the three proposed GDIT domains of gambling behavior, gambling symptoms, and negative consequences. Receiver operator curves and clinical significance indicators were used to estimate GDIT cut-off scores in relation to recreational (<15) and problem gambling (15-19), any GD (≥20), mild GD (20-24), moderate GD (25-29), and severe GD (≥30). The GDIT can be considered a valid and reliable measure to identify and predict GD severity, as well as problem gambling. In addition, the GDIT improves content validity in relation to an international research agreement concerning features of gambling outcome measures, known as the Banff Consensus Agreement. SAGE Publications 2021-10-07 2023-01 /pmc/articles/PMC9684656/ /pubmed/34617456 http://dx.doi.org/10.1177/10731911211046045 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/This article is distributed under the terms of the Creative Commons Attribution 4.0 License (https://creativecommons.org/licenses/by/4.0/) which permits any use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages (https://us.sagepub.com/en-us/nam/open-access-at-sage). |
spellingShingle | Articles Molander, Olof Wennberg, Peter Berman, Anne H The Gambling Disorders Identification Test (GDIT): Psychometric Evaluation of a New Comprehensive Measure for Gambling Disorder and Problem Gambling |
title | The Gambling Disorders Identification Test (GDIT): Psychometric
Evaluation of a New Comprehensive Measure for Gambling Disorder and Problem
Gambling |
title_full | The Gambling Disorders Identification Test (GDIT): Psychometric
Evaluation of a New Comprehensive Measure for Gambling Disorder and Problem
Gambling |
title_fullStr | The Gambling Disorders Identification Test (GDIT): Psychometric
Evaluation of a New Comprehensive Measure for Gambling Disorder and Problem
Gambling |
title_full_unstemmed | The Gambling Disorders Identification Test (GDIT): Psychometric
Evaluation of a New Comprehensive Measure for Gambling Disorder and Problem
Gambling |
title_short | The Gambling Disorders Identification Test (GDIT): Psychometric
Evaluation of a New Comprehensive Measure for Gambling Disorder and Problem
Gambling |
title_sort | gambling disorders identification test (gdit): psychometric
evaluation of a new comprehensive measure for gambling disorder and problem
gambling |
topic | Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9684656/ https://www.ncbi.nlm.nih.gov/pubmed/34617456 http://dx.doi.org/10.1177/10731911211046045 |
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