Disordered gambling, or dependence and consequences: a bifactor exploratory structural equation model analysis of the problem gambling severity index.
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| Title: | Disordered gambling, or dependence and consequences: a bifactor exploratory structural equation model analysis of the problem gambling severity index. |
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| Authors: | James, Richard J. E., Tillsley, Jaimie E., Hitcham, Lucy, Mou, Cong, Kim, Hyungseo, Tunney, Richard J. |
| Source: | Addiction Research & Theory. Apr2025, Vol. 33 Issue 2, p122-133. 12p. |
| Subjects: | Compulsive behavior -- Risk factors, Risk assessment, Compulsive behavior, Secondary analysis, Research methodology evaluation, Gambling, Descriptive statistics, Structural equation modeling, Chi-squared test, Surveys, Research, Research methodology, Data analysis software |
| Geographic Terms: | United Kingdom |
| Abstract: | Background: The Problem Gambling Severity Index (PGSI) is a widely used assessment of disordered gambling. However, it has been claimed that instead of measuring a single factor of problem gambling severity, the PGSI measures two correlated factors of behavioral dependence and harms/consequences. The existing literature using exploratory and confirmatory factor analysis has notable limitations that mean these accounts cannot be discriminated. Method: Secondary data from 13 nationally representative surveys of gamblers in the UK (n = 42,422) between 2007 and 2023 were used to examine five different approaches to specifying one- and two-factor models of the PGSI. Results: Overall, the findings supported a single construct account. Fit indices provided slight support for a two-factor model. However, the composition and loadings of these factors did not replicate in the disaggregated datasets and demonstrated poor model-based reliability. The best-fitting model was a bifactor ESEM model with a general gambling severity factor and a group-specific factor subsuming additional covariance between the first three or four items. Conclusions: This study provides support for a unitary gambling severity construct and the use of total PGSI scores. The second factor observed elsewhere appears to consist of residual covariances between the first 3-4 PGSI items or a methods factor that can be explained by item framing (e.g. items that ask about gambling behavior). [ABSTRACT FROM AUTHOR] |
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| Database: | Psychology and Behavioral Sciences Collection |
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| Abstract: | Background: The Problem Gambling Severity Index (PGSI) is a widely used assessment of disordered gambling. However, it has been claimed that instead of measuring a single factor of problem gambling severity, the PGSI measures two correlated factors of behavioral dependence and harms/consequences. The existing literature using exploratory and confirmatory factor analysis has notable limitations that mean these accounts cannot be discriminated. Method: Secondary data from 13 nationally representative surveys of gamblers in the UK (n = 42,422) between 2007 and 2023 were used to examine five different approaches to specifying one- and two-factor models of the PGSI. Results: Overall, the findings supported a single construct account. Fit indices provided slight support for a two-factor model. However, the composition and loadings of these factors did not replicate in the disaggregated datasets and demonstrated poor model-based reliability. The best-fitting model was a bifactor ESEM model with a general gambling severity factor and a group-specific factor subsuming additional covariance between the first three or four items. Conclusions: This study provides support for a unitary gambling severity construct and the use of total PGSI scores. The second factor observed elsewhere appears to consist of residual covariances between the first 3-4 PGSI items or a methods factor that can be explained by item framing (e.g. items that ask about gambling behavior). [ABSTRACT FROM AUTHOR] |
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| ISSN: | 16066359 |
| DOI: | 10.1080/16066359.2024.2352094 |
