The Association Between Stress and Social Decision-Making

Context. To navigate the world, we need to understand others—their knowledge of the world and intentions. However, interacting with others is uncertain: we do not know how individuals will react to us— although we might have prior expectations of how others might behave. To make "good decisions," we must learn about our environment and update information when necessary. As if decision-making alone was not tricky enough; external factors—such as stress— influence these processes. Stress, a daily occurrence in life, has been shown to change decision-making, specifically in social contexts. However, findings are inconsistent, mainly due to heterogeneity in methods to assess learning and decision-making while relying on static environments. Furthermore, acute stress and lifestress are often treated synonymously despite not being analogs. Research on acute stress thus has limited applicability when trying to understand the effects of lifestress. Objective. Here, we propose a series of studies to elucidate the association between stress and social decision-making. We hypothesize that various forms of stress will impact decision-making differentially, distinctively impacting learning and updating of information. As such, higher levels of lifestress will be associated with a higher negativity bias and—as indicated by pilot data—lower trust in social information; acute stress will be associated with a higher belief in the volatility of the world, resulting in more frequent updating. Acute stress will result in more reliance on social information (particularly in noisy environments). Methods. Over 3 studies, we will investigate the effects of various types of stress on social decision-making. We will use a bandit task where participants must learn about their environment. To model social information processing, we will add a layer of social information, an actor with previous knowledge of the decision space (a computer algorithm) who can be monitored for additional information. Furthermore, the decision space will be volatile, as contingencies will change over time, requiring updating of information for accuracy. To understand decision-making, we will use the Hierarchical Gaussian Filter (HGF) to derive latent decisionmaking parameters. The HGF allows for modelling parameters associated with uncertainty, providing a comprehensive approach to understanding decisions and biases. Originality. This project will be the first to investigate the effects of stress—in various forms—on social decision-making using a state-of-the-art computational approach. This will help delineate the effects of multiple types of stress on decision-making and shed light on the impact of stress on dealing with volatility. By its methodological approach, this project will also pave the way for future studies investigating the relationship between stress and sociality more extensively. Researchers. J. Nitschke, C. Lamm, N. Mikus, C. Mathys, G. Slavich