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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.
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]
Copyright of Addiction Research & Theory is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Psychology and Behavioral Sciences Collection
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  Data: Disordered gambling, or dependence and consequences: a bifactor exploratory structural equation model analysis of the problem gambling severity index.
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  Data: 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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  Data: <i>Copyright of Addiction Research & Theory is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.1080/16066359.2024.2352094
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      – Code: eng
        Text: English
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      Pagination:
        PageCount: 12
        StartPage: 122
    Subjects:
      – SubjectFull: Compulsive behavior -- Risk factors
        Type: general
      – SubjectFull: Risk assessment
        Type: general
      – SubjectFull: Compulsive behavior
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      – SubjectFull: Research methodology evaluation
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      – SubjectFull: Gambling
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      – SubjectFull: Descriptive statistics
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      – SubjectFull: Structural equation modeling
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      – SubjectFull: Chi-squared test
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      – SubjectFull: United Kingdom
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              Text: Apr2025
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