Validating the Two-Factor Model of the Gambling Functional Assessment – Revised in a Mainland Chinese sample

Kimberly Tom, Xun Zhu, Hsuan-Ying Liu, Jeffrey Weatherly

Research output: Contribution to journalArticlepeer-review


The Gambling Functional Assessment – Revised (GFA-R) was developed to measure the degree to which gambling behavior is maintained by positive reinforcement and/or negative reinforcement. In the current study, the GFA-R, South Oaks Gambling Screen, and Problem Gambling Severity Index were translated into simplified Chinese and completed by university students from mainland China (N = 299). A confirmatory factor analysis was conducted on a subset of the sample who scored greater than 0 on the GFA-R (N = 112). Results of the confirmatory factor analysis revealed the previously validated two-factor model of the original GFA-R (i.e., positive reinforcement & negative reinforcement) adequately fit the data from the current sample. Five of the items from the GFA-R did not adequately load to either factor; cultural factors and translation issues were discussed as possible explanations. Consistent with previous research, gambling maintained by negative reinforcement was found to be more strongly correlated with gambling problems than gambling maintained by positive reinforcement. These results indicate the Chinese version of the GFA-R may be useful for identifying maintaining contingencies for gambling behavior in Chinese populations, which may be beneficial to practitioners when attempting to treat gambling problems.
Original languageAmerican English
Pages (from-to)1-15
Number of pages15
JournalJournal of Gambling Issues
StatePublished - Dec 20 2022


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