Investigation of impulsivity in a sample of treatment-seeking pathological gamblers: a multidimensional perspective

A Revised Model of Dickman’s Dysfunctional Impulsivity Scale

The literature suggests limitations to Dickman’s dysfunctional impulsivity (DI) scale. These concerns are centered on the measurement properties of this scale and on its reliance on student samples. To address these criticisms, the DI was administered to a random adult sample (n = 649, mean age 43.83 ± 13.46 years), 13% of whom were university educated. Confirmatory factor analysis (CFA) did not support the fit of the posited 12-item DI scale. The full sample was randomly divided. Principal components analysis was applied to one sample (n = 328), resulting in a 9-item model. This new model was then replicated using CFA in the second sample (n = 321). Cronbach’s α for the 9-item model was 0.84 and item-total correlations were > 0.39. The 30th and 70th percentile scores from the DI distribution of scores were used to categorize participants with low and high DI. The high-DI group was associated with significantly more driving distractions and lane crossings.

Are the effects of response inhibition on gambling long-lasting?

A recent study has shown that short-term training in response inhibition can make people more cautious for up to two hours when making decisions. However, the longevity of such training effects is unclear. In this study we tested whether training in the stop-signal paradigm reduces risky gambling when the training and gambling task are separated by 24 hours. Two independent experiments revealed that the aftereffects of stop-signal training are negligible after 24 hours. This was supported by Bayes factors that provided strong support for the null hypothesis. These findings indicate the need to better optimise the parameters of inhibition training to achieve clinical efficacy, potentially by strengthening automatic associations between specific stimuli and stopping.