Benchmarking gambling screens to health-state utility: the PGSI and the SGHS estimate similar levels of population gambling-harm

Background Both the Problem Gambling Severity Index (PGSI) and the Short Gambling Harms Screen (SGHS) purport to identify individuals harmed by gambling. However, there is dispute as to how much individuals are harmed, conditional on their scores from these instruments. We used an experienced utility framework to estimate the magnitude of implied impacts on health and wellbeing. Methods We measured health utility using the Short Form Six-Dimension (SF-6D), and used this as a benchmark. All 2603 cases were propensity score weighted, to balance the affected group (i.e., SGHS 1+ or PGSI 1+ vs 0) with a reference group of gamblers with respect to risk factors for gambling harm. Weighted regression models estimated decrements to health utility scores attributable to gambling, whilst controlling for key comorbidities. Results We found significant attributable decrements to health utility for all non-zero SGHS scores, as well as moderate-risk and problem gamblers, but not for PGSI low-risk gamblers. Applying these coefficients to population data, we find a similar total burden for both instruments, although the SGHS more specifically identified the subpopulation of harmed individuals. For both screens, outcomes on the SF-6D implies that about two-thirds of the ‘burden of harm’ is attributable to gamblers outside of the most severe categories. Conclusions Gambling screens have hitherto provided nominal category membership, it has been unclear whether moderate or ‘at-risk’ scores imply meaningful impact, and accordingly, population surveys have typically focused on problem gambling prevalence. These results quantify the health utility decrement for each category, allowing for tracking of the aggregate population impact based on all affected gamblers.