Disordered gambling, or dependence and consequences: a bifactor exploratory structural equation model analysis of the problem gambling severity index

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).