| Summary: | 1. Abstract Affective forecasting refers to the process of predicting emotional reactions to future \ . events. Affective forecasting plays an important role in decision making as it informs \ subjective utility, but it is also prone to prediction errors, such as the 'impact bias': a tendency to overestimate the intensity and duration of future emotional reactions. It has been argued that the impact bias can be considered to be evolutionarily adaptive, as it performs a protective function in motivating people to avoid risky behaviour. Problem gambling (PG) is a serious public health problem and yet knowledge about this disorder is still limited. There is evidence to suggest that affective forecasting may be qualitatively different in a risk-taking population such as problem gamblers (PGs). In particular, PGs may fail to show the impact bias, thus helping to explain their persistence in behaviours resulting in losses. This study was the first to examine affective forecasting in PGs. Following an adapted version of a procedure used by Kermer, Driver-Linn, Wilson & Gilbert (2006), PGs (N=25) and matched controls (N=29) were asked to rate their affect currently and to predict how they would feel after completing a simple computerized guessing task. Control participants exaggerated how bad they would feel after losing at the guessing task (i.e., they displayed the impact bias), whereas PGs accurately predicted their emotional reactions. This, and other results, has been discussed within the context of existing theories of gambling addiction and suggestions have been made for future 6 \ research. The thesis concluded that that encouraging PGs to focus on anticipated emotions may be a novel target for existing treatment interventions. 7
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