Development of the online imitation-inhibition task to investigate modulations of automatic imitation
Year: 2024
Type: dissertation
Abstract: People automatically imitate a wide range of different behaviors. One of the most commonly used measurement methods to assess imitative behavior is the imitation-inhibition task (Brass et al., 2000). However, in its original form, the task is only suited to be carried out in a laboratory setting – a time-consuming and costly procedure. In this dissertation, I will present a method for investigating automatic imitation in an online environment (i.e., introducing an online imitation-inhibition task). This online version allows for a more economically investigation of automatic imitation. Using this task, I investigated different modulations to address theoretically relevant questions and contribute to the research field of automatic imitation. Specifically, there have been problems replicating some findings with the imitation-inhibition task recently, particularly regarding findings that involved social modulations. This is likely due to the fact that social effects with the imitation-inhibition task are very small. However, the online-imitation task provides an opportunity to examine the impact of social and other modulations on automatic imitation with high statistical power. It can thus be used to detect very small effect sizes. In six chapters, I will first review the literature on automatic imitation. I will then test the impact of different social and non-social modulations (i.e., belief in free will, finger movement size, finger movement speed, animacy beliefs, and group membership) on automatic imitation using the online imitation-inhibition task. Finally, I will discuss possible reasons for the failed and successful replications and provide further insight into possible explanations and implications.
Author: Westfal, Mareike
Institutions: Leuphana University of Lüneburg, University of Cologne
Language: English
Subfield: Social Psychology
Field: Psychology
Domain: Social Sciences
Open Access status: green
Funder: Deutsche Forschungsgemeinschaft
Award: G2369972262
OpenAlex ID: W7018367776