Gambling habits and Probability Judgements in a Bayesian Task Environment.

Abstract

Little is known about how gamblers form probability assessments. This paper reports on a preregistered study that administered an incentivized Bayesian choice task to n = 465 self-reported gamblers and non-gamblers. The task elicits subjective probability assessments and allows one to estimate the degree to which distinct information sources are weighted in forming probability assessments. Our data failed to support our main hypotheses that experienced online gamblers would be more accurate than non-gamblers in estimating probabilities, that gamblers experienced in games of skill (e.g., poker) would be more accurate than gamblers experienced only in non-skill games (e.g., slots), that accuracy would differ by sex, or that information sources would be weighted differently across different participant groups. Exploratory analysis, however, revealed that gambling frequency predicted lower Bayesian accuracy, while cognitive reflection predicted higher accuracy. The decline in accuracy linked to self-reported gambling frequency was stronger for female participants. Decision modeling estimated a decreased weight place on new evidence (over base rate odds) for those participant groups who showed decreased accuracy, which suggests that a proper incorporation of new information is important for probability assessments. Our results link online gambling frequency to worse performance in the critical probability assessment skills that should benefit gambling success (i.e., in skill-based games). Additional research is needed to better understand the mechanism linking reported gambling frequency to probability assessment accuracy.