Measuring implicit bi-dimensional attitudes and predicting speeding behaviour

Attitudes are bi-dimensional predictors of behaviour, meaning that attitudes comprise separate positive and negative dimensions, which both predict behaviour independently (Elliott et al., 2015). Furthermore, the positive dimension of attitude is the stronger predictor for risky behaviours (e.g., speeding). This implies that evaluative beliefs about positive behavioural consequences strongly influence subsequent behavioural performance. Beliefs about negative behavioural consequences do not. In previous research, bi-dimensional attitudes have been measured using questionnaires, which tap explicit cognitive judgements. However, implicit cognitive processes are likely to dictate the performance of habitual behaviours such as speeding. We therefore measured bi-dimensional attitudes using an implicit association test (IAT). The presentation will cover the development of the IAT and the results from regression modelling, in which test performance was used to predict speeding behaviour. The implications for better understanding the cognitive processes that dictate behavioural performance and how to change behaviour will be discussed.