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Further Exploration of the Psychometric Properties of GamTest: A Rasch Analysis

Author

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  • David Forsström

    (Department of Psychology, Stockholm University, Frescati Hagväg 8, 105 90 Stockholm, Sweden
    Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet & Stockholm Health Care Services, Region Stockholm, Norra Stationsgatan 69, 113 64 Stockholm, Sweden)

  • Alexander Rozental

    (Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet & Stockholm Health Care Services, Region Stockholm, Norra Stationsgatan 69, 113 64 Stockholm, Sweden
    UCL, Great Ormond Street, Institute of Child Health, London WC1N 1EH, UK)

  • Anders Kottorp

    (Faculty of Health and Society, Malmö University, Jan Waldenströms Gata 25, 214 28 Malmö, Sweden)

  • Philip Lindner

    (Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet & Stockholm Health Care Services, Region Stockholm, Norra Stationsgatan 69, 113 64 Stockholm, Sweden
    Centre for Dependency Disorders, Stockholm Health Care Services, 104 31 Stockholm, Sweden)

  • Markus Jansson-Fröjmark

    (Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet & Stockholm Health Care Services, Region Stockholm, Norra Stationsgatan 69, 113 64 Stockholm, Sweden)

  • Hugo Hesser

    (School of Law, Psychology and Social Work, Örebro University, 701 82 Örebro, Sweden
    Department of Behavioural Sciences and Learning, Linköping University, 581 83 Linköping, Sweden)

Abstract

GamTest is a self-rating scale of negative consequences of gambling, included in the popular responsible gambling tool Playscan as part of an overall risk assessment and feedback feature. Two previous psychometric evaluations of this instrument yielded contradictory results: in an online high-gambling population, a five-factor model was supported and the instrument had overall good psychometric properties, but in a low-gambling population, the same factor structure was not supported. Because GamTest is used with both low- and high-gambling populations, more psychometric research is needed to fully understand how the instrument works. The current study examined, for the first time, psychometric performance among a sample of low-gambling respondents using a Rasch analysis. Results indicated that the instrument could be improved by decreasing the scale-steps and removing several problematic items demonstrating misfit. Furthermore, the findings indicated that some items functioned differently depending on gender, and that a shortened, improved nine-item version could not differentiate between different levels of risk. Our findings suggest that the instrument would arguably benefit from being adapted for use in a low-gambling population.

Suggested Citation

  • David Forsström & Alexander Rozental & Anders Kottorp & Philip Lindner & Markus Jansson-Fröjmark & Hugo Hesser, 2021. "Further Exploration of the Psychometric Properties of GamTest: A Rasch Analysis," IJERPH, MDPI, vol. 18(9), pages 1-12, April.
    • Handle: RePEc:gam:jijerp:v:18:y:2021:i:9:p:4824-:d:547274
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    References listed on IDEAS

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    1. Jim Orford & Heather Wardle & Mark Griffiths & Kerry Sproston & Bob Erens, 2010. "PGSI and DSM-IV in the 2007 British Gambling Prevalence Survey: reliability, item response, factor structure and inter-scale agreement," International Gambling Studies, Taylor & Francis Journals, vol. 10(1), pages 31-44, April.
    2. Stéphanie Baggio & Sally M. Gainsbury & Vladan Starcevic & Jean-Baptiste Richard & François Beck & Joël Billieux, 2018. "Gender differences in gambling preferences and problem gambling: a network-level analysis," International Gambling Studies, Taylor & Francis Journals, vol. 18(3), pages 512-525, September.
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