An Action Dynamics Approach to Assessing Potential Implicit Biases Toward Transgender People

To reveal opinions people may not explicitly portray, researchers have implemented a methodology called the Implicit Associations Test (IAT). While this test saw widespread use after its inception, recent problems have undermined the reliability of the measure. Researchers have begun to address these limitations by evaluating different approaches, such as the Action Dynamics paradigm. Like the IAT, the aim of action dynamics is to assess underlying activation and competition amongst beliefs as they unfold in real-time, while adding a number of more sensitive measures, in addition to those used in an IAT. The trajectories of participants’ computer mouse cursors are tracked as they move from a stimulus statement to a response, providing data of the real-time decisions people are making across a number of variables. For this thesis study, the aim was to use an action dynamics paradigm to explore whether implicit biases exist toward transgender people from a larger cisgender population, even if they explicitly support or oppose others with transgender identities. These potential biases were assessed by evaluating the statements people were asked to confirm or disconfirm. There were also a number of analyses conducted in order to investigate whether such predictors such as participants’ gender or political ideology predicted differences in responses. Although differences were seen in the reaction time to statements of a certain category, the other trajectory measures showed that participants’ implicit and explicit attitudes toward transgender people were aligned. Implications, limitations, and future directions of this work are then discussed.