Decision Making in Chronic Pain: The Role of Punishments and Rewards

Abstract

Introduction Chronic pain (i.e., subjective feeling of pain in absence of bodily problems) is associated with major distress for individuals and high economic costs for the society. Understanding the nature of chronic pain could help in building better treatments, and as such reduce the individual distress and the societal costs. Here, we aim to gain more insight on chronic pain by investigating potential biases in decision making. Specifically, daily individuals either stick to decisions they have made before (e.g., choosing a restaurant where they have eaten before), or choose something different (e.g., go to a new restaurant). This so-called explore/exploit dilemma has been widely tested in the context of rewards (e.g., addiction literature). Alas, there is scarce research of explore/exploit dilemmas in the context ofchronic pain. Importantly, biases in explore/exploit decisions are to be expected given that often individuals with chronic pain symptomatology will stick to a dysfunctional behavior (e.g., kneeling rather than bending for avoiding ‘breaking’ their back) rather than explore alternative behaviors. Method Here, we present the results of three experiments in which we tested a novel experimental paradigm for testing explore/exploit dilemmas in pain. Participants had to freely move a joystick towards 4 different places on the screen (top, down, right, left). Importantly, each movement was associated with different probabilities of receiving a painful shock (Experiment 1), or a painful shock together with rewarding points (Experiment 2). We also tested whether individuals will update their preferences towards each movement after changing the associations between each movement and the probability of receiving a painful stimulus together with rewarding points (Experiment 3). Results For each experiment we fitted different computational models for describing participants’ behaviour, as well as correlated the model parameters with a series of individual difference questionnaires (e.g., intolerance of uncertainty, fear of pain). We performed all our analysis using the programming language R and Stan. In the poster we present the model that described each experiment best, as well as the correlation between the parameters of the best-fitting model and the collected individual differences characteristics. Discussion Our results could help in better understanding decision-making in pain contexts, and also test how such decision-making biases may be different compared to other situations (e.g., in case of appetitive stimuli only). Such knowledge is particularly important towards the better development of treatment protocols for chronic pain.