1. A predictive processing account of problem gambling

Thursday, 24 November, 2022 - 16:50 to 18:20


Predictive processing (PP) is a recent theoretical framework in the mind sciences, increasingly used to address both pathological and nonpathological behaviours. It considers the reduction of uncertainty a key task in any human endeavour. Uncertainty is reduced by increasing the model fit between our internal predictions and the external environment by either updating our prior beliefs or by acting upon the world. Despite being applied to addiction in general and various other psychiatric disorders, a thorough account for problem gambling has been lacking. We contend that casting gambling as a problem of PP provides an especially informative viewpoint with practical implications.

A theoretical account of problem gambling is developed through the lens of PP. A critical assessment of the merits of this account based on research literature is provided.

PP avoids the problem of casting people who gamble as irrational, as it considers the behaviour as boundedly rational given their experience. By focusing on the phenomena of illusion of control and near-miss situations we showcase how uncertainty reduction could distinguish between problematic and recreational gambling.

We propose the PP framework to provide a novel view of practical value on problem gambling, which helps us understand how the internal processes and contextual factors interplay. We briefly discuss its possible treatment and policy implications.


Presentation files

24 5B 1650 Jarno Tuominen_v1.0.pdf293.43 KBDownload



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