The problem gambling measure: a revision of the problem & pathological gambling measure to better predict at-risk and chronic gambling

ABSTRACT

Most problem gambling (PG) assessment instruments classify individuals with subthreshold levels of problem gambling symptomatology as ‘at-risk’, implying a future risk of developing more serious problems. However, this convention lacks empirical support. The present study aimed to develop an empirically supported revision of the Problem and Pathological Gambling Measure (PPGM) that (1) better assesses the risk of future gambling-related harm (GRH) and PG as well as (2) better predicts cases in which PG persists. Data from the Alberta Gambling Research Institute’s National Project Baseline and Follow-up Online Panel Surveys (n = 4676) were used to identify predictors of future GRH and PG. Five variables maximized prediction power: PPGM total score, problem perception, rated importance of gambling as a leisure activity, largest single day gambling loss, and breadth of monthly gambling involvement. A 16-point scale was produced based on the relative risk of developing GRH and PG and Receiver Operating Characteristic (ROC) analyses found that scores of 1, 4, and 8 best captured a gradient of risk for future GRH or PG. Regarding chronicity, a total score of 7 and higher was found to be most parsimoniously predictive of chronic PG. The revised instrument was renamed the Problem Gambling Measure (PGM).

KEYWORDS:

• Problem gambling
• gambling-related harm
• assessment
• longitudinal
• chronicity

Disclosure statement

No potential conflict of interest was reported by the author(s).

Data availability statement

The data that support the findings of this study are openly available in the GREO’s data repository, https://doi.org/10.5683/SP3/JYUO8E.

Notes

1. These investigations documented that impaired control over gambling is a separate dimension from gambling problems (these dimensions are separately assessed in the PPGM).

2. The DSM-5-TR (American Psychiatric Association [APA], 2022), NODS, and the SOGS do not explicitly employ an ‘at-risk’ designation.

3. There is a degree of circularity in the inclusion of PPGM total score as a predictor, as you need a minimum total score of 1 to have GRH and usually a minimum total score of 2 to have PG. This is likely part of the reason why this variable was the strongest predictor. (The circularity is reduced somewhat by the fact that everyone who met criteria for GHR and/or PG at Baseline was excluded from the analysis, thus PPGM total score had a zero baseline cross-sectional relationship with GRH and PG). It was included as a predictor because it is a measure of subclinical GRH and PG symptomatology, which has historically been the default criteria for the ‘at-risk’ categorization (i.e. it was necessary to establish the degree to which this traditional criterion was still useful).

4. That said, a recent Canadian investigation determined that there were no unique risk factors for problem gambling among Indigenous Canadians, but rather their elevated rates of PG were due to elevated rates of the common risk factors (Williams, Belanger, et al., 2021).

5. A lifetime history of problem gambling is also known to be a reliable risk factor for problem gambling continuation and relapse (e.g. MAGIC Research Team, 2021).

6. Simplest way of establishing this is by using the highest frequency of gambling reported for any individual form in the past year.

7. Sometimes gambling expenditure is collected by asking about both losses on gambling and winning on gambling. In this situation it is best to use the reported losses figure rather than net losses figure, as it tends to be a more accurate estimate of true losses, especially among problem gamblers.

Additional information

Funding

The online panel survey was jointly funded by the Canadian Centre on Substance Use and Addiction, Gambling Research Exchange Ontario (GREO), and the Alberta Gambling Research Institute.

Notes on contributors

Nolan B. Gooding

Nolan B. Gooding is a Master of Science student in the department of psychology at the University of Lethbridge. His research interests include gambling, substance use, and addictive disorder.

Robert J. Williams

Robert J. Williams is a Professor of Health Sciences at the University of Lethbridge and a Coordinator with the Alberta Gambling Research Institute.

Rachel A. Volberg

Rachel A. Volberg is a Research Professor in the School of Public Health and Health Sciences at the University of Massachusetts Amherst. She has been involved in research on gambling and problem gambling since 1985.