Our decisions are often made within social contexts, and our behaviour and beliefs are subject to change due to the influence of other individuals or groups. Contagion is an implicit social influence effect whereby learning about others makes us more like them, and contagion effects have been found in discounting tasks. However, little research has explored individual differences in this effect. The key aim of this thesis is to investigate these differences. Across four experimental chapters, a Bayesian neurocomputational approach was used to examine contagion, and each chapter focuses on different aspects of individual differences in this effect. In chapter 3, contagion of temporal discounting preferences was explored in two neurotypical samples, and one sample of autistic adults. In chapter 4, similarities and differences between contagion of temporal and probability discounting preferences were explored. In chapter 5, the effect of social distance on contagion was explored in an fMRI study. In chapter 6, an online study was conducted to explore the relationship between temporal discounting contagion, and advice-taking and choice behaviour in a social probabilistic reward learning task. In all chapters, a significant contagion effect was found, indicating that contagion is a strong and reproducible effect. However, none of the studies presented within this thesis were able to index individual differences in contagion. No group differences were found between neurotypical and autistic participants, and no significant relationship was observed between autistic traits and contagion in neurotypical samples. A significant relationship between contagion and accuracy was also not found, and contagion also did not significantly differ dependent on the identity of the other agent, despite finding an effect of social distance on learning and feedback processing. In the general discussion, further ideas for exploring individual differences in this effect are explored.
|Award date||1 Aug 2021|
|Publication status||Submitted - 2021|
- Social influence
- Bayesian computational modelling
- Computational modelling
- Temporal discounting
- Probability discounting