How to trust when lonely? The effects of loneliness on behaviors and expectations in trusting interactions

Perceived social isolation (e.g., loneliness) is a major contributing factor to reduced well- being. Approximately 15-30% of people suffer from prolonged feelings of loneliness with severe implications for physical and mental health. Previous work has theorized that loneliness arises as a warning signal to prompt individual to connect. However, empirical evidence, especially in clinical psychology, suggests that loneliness decreases an individual’s odds of being successfully embedded in a social group. Despite its essential social nature, little experimental work has done to unearth the effects of loneliness on social behaviors and expectations. Across different studies and with the help of different methodologies (e.g., survey data, economic games and neuroimaging techniques), we investigated the effects of loneliness on socially-relevant expectations of others and elucidated how these effects reverberate in the concomitant social behaviors. In particular, we focused on trustworthiness expectations and trusting behaviors during interactive social paradigms. We show that loneliness has positive effects on prosocial behaviors but negative effects on social expectations of others. Specifically, lonelier individuals trusted more their partners despite expecting them to be less trustworthy. These effects were mediated by extraversion, which mitigated the negative effects of loneliness on trustworthiness expectations. In lonelier individuals, these effects were accompanied by a negative bias toward untrustworthy behaviors of others and reduced neural activity in the orbitofrontal cortex for feedback about their trustworthy behavior. Taken together, these findings demonstrate how loneliness operates and impacts social expectations, social behaviors and their underlying neural, psychological and computational processes. As a result, this work will help understand the early dynamics of different psychiatric conditions strongly predicted by loneliness states (e.g., depression), potentially contributing to better diagnosis, prevention and treatment of clinical disorders