Assessing gambling disorder using frequency‐ and time‐based response options: A Rasch analysis of the gambling disorder identification test

• Published in: International journal of methods in psychiatric research Vol. 33; no. 1; pp. e2018 - n/a
• Main Authors: Molander, Olof, Wennberg, Peter, Dowling, Nicki A., Berman, Anne H.
• Format: Journal Article
• Language: English
• Published: United States John Wiley and Sons Inc 01.03.2024; Wiley
• Subjects: Diagnostic and Statistical Manual of Mental Disorders; DSM-5; Gambling - diagnosis; gambling disorder; Humans; item difficulty; Original; Psychometrics; Rasch analysis; Reproducibility of Results; Self Report; Surveys and Questionnaires; the gambling disorder identification test; Rasch analysis; DSM-5; gambling disorder; item difficulty; the gambling disorder identification test
• ISSN: 1049-8931; 1557-0657; 1557-0657
• DOI: 10.1002/mpr.2018

Objectives The Gambling Disorder Identification Test (GDIT) is a recently developed self‐report measure. The GDIT includes items with multiple response options that are either based on frequency or time, and item response theory evaluations of these could yield vital knowledge on its measurement performance. Methods The GDIT was evaluated using Rasch analysis in a study involving 597 Swedish gamblers. Results In a three‐dimensional Rasch model, the item response difficulty range extended from −1.88 to 4.06 and increased with higher time‐ and frequency‐based responses. Differential item functioning showed that some GDIT items displayed age and gender‐related differences. Additionally, person‐separation reliability indicated the GDIT could reliably be divided into three to four diagnostic levels. Conclusions The frequency‐ and time‐based item response options of the GDIT offer excellent measurement, allowing for elaborate assessment across both lower and higher gambling severity. The GDIT can be used to detect DSM‐5 Gambling Disorder, thereby holding significance from both epidemiological and clinical standpoints. Notably, the 3‐item GDIT Gambling Behavior subscale also shows potential as a brief screening tool for identifying at‐risk gambling behavior.