ArticleInternational journal of methods in psychiatric research2024
Assessing gambling disorder using frequency- and time-based response options: A Rasch analysis of the gambling disorder identification test.
Article in International journal of methods in psychiatric research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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3 citing papers in PubMed, 6 citations in OpenAlex.
- Distinguishing Persistent Versus Episodic Clusters of At-Risk Respondents on the Problem Gambling Severity Index.Journal of gambling studies · 2025Article
- Striving Towards National Lower-Risk Gambling Guidelines: An Empirical Investigation Among a Sample of Swedish Gamblers.Journal of gambling studies · 2025Article
- Assessing gambling disorder using frequency- and time-based response options: A Rasch analysis of the gambling disorder identification test.International journal of methods in psychiatric research · 2024Article
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Authors and funding
4 authors at 4 institutions in 3 countries.
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Abstract
objectivesThe 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.
methodsThe GDIT was evaluated using Rasch analysis in a study involving 597 Swedish gamblers.
resultsIn 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.
conclusionsThe 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.
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