IDEAS home Printed from https://ideas.repec.org/a/taf/intgms/v23y2023i3p403-417.html
   My bibliography  Save this article

Assessing severity of problem gambling – confirmatory factor and Rasch analysis of three gambling measures

Author

Listed:
  • Olof Molander
  • Peter Wennberg

Abstract

The comparative psychometric properties of self-report measures for gambling are insufficiently evaluated, in particular regarding factor structure and item response properties. Confirmatory factor and Rasch analyses were tested for three widely used gambling measures assessing problem gambling and related constructs, that is, the Problem Gambling Severity Index (PGSI), the Problem and Pathological Gambling Measure (PPGM), and the NORC Diagnostic Screen for Gambling Problems (NODS). Psychometric data was analyzed, including help-seeking and recreational gambling samples (N = 598). Compared to the PPGM and the NODS, the PGSI performed worse in the confirmatory factor analysis, and showed poor fit for the theoretically assumed unidimensional model. The Rasch analysis indicated that the PPGM had an adequate difficulty range (i.e. lowest to highest item difficulty) to detect gambling problems across a severity continuum. Compared to the PPGM, the PGSI and NODS had smaller item difficulty ranges, indicating detection of higher gambling severity problems. We conclude that using the PGSI for detection of low severity problems, such as at-risk gambling, might be problematic. The PPGM can be used in general populations and clinical contexts to detect problem gambling and pathological gambling. The NODS is suitable for use in clinical samples for identification of pathological gambling.

Suggested Citation

  • Olof Molander & Peter Wennberg, 2023. "Assessing severity of problem gambling – confirmatory factor and Rasch analysis of three gambling measures," International Gambling Studies, Taylor & Francis Journals, vol. 23(3), pages 403-417, September.
  • Handle: RePEc:taf:intgms:v:23:y:2023:i:3:p:403-417
    DOI: 10.1080/14459795.2022.2149834
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/14459795.2022.2149834
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1080/14459795.2022.2149834?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:taf:intgms:v:23:y:2023:i:3:p:403-417. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/RIGS20 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.