biostudies-literatureMolander OForte, the Swedish Research Council for Health, Working Life and WelfareDevelopment funds for identification and treatment of problem gambling from the Stockholm Health Care Services, Stockholm Region225-237https://www.ebi.ac.uk/biostudies/studies/S-EPMC9684656biostudies-literatureUnknown30(1)The novel gambling disorder identification test (GDIT) was recently developed in an international Delphi and consensus process. In this first psychometric evaluation, gamblers (<i>N</i> = 603) were recruited from treatment- and support-seeking contexts (<i>n</i> = 79 and <i>n</i> = 185), self-help groups (<i>n</i> = 47), and a population sample (<i>n</i> = 292). Participants completed self-report measures, a GDIT retest (<i>n</i> = 499), as well as diagnostic semistructured interviews assessing gambling disorder (GD; <i>n</i> = 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.AssessmentThe Gambling Disorders Identification Test (GDIT): Psychometric Evaluation of a New Comprehensive Measure for Gambling Disorder and Problem Gambling.PMC96846562016-07091Wennberg PBerman AHMolander OfalseThe 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 (<i>N</i> = 603) were recruited from treatment- and support-seeking contexts (<i>n</i> = 79 and <i>n</i> = 185), self-help groups (<i>n</i> = 47), and a population sample (<i>n</i> = 292). Participants completed self-report measures, a GDIT retest (<i>n</i> = 499), as well as diagnostic semistructured interviews assessing gambling disorder (GD; <i>n</i> = 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.2023-01-01T00:00:00Z2023 Jan2025-04-05T15:21:18.999Z2025-04-05T15:21:18.999ZS-EPMC96846563461745610.1177/10731911211046045