Predicting affective choice.

Affect is increasingly recognized as central to decision making. However, it is not clear whether affect can be used to predict choice. To address this issue, we conducted 4 studies designed to create and test a model that could predict choice from affect. In Study 1, we used an image rating task to develop a model that predicted approach-avoidance motivations. This model quantified the role of two basic dimensions of affect--valence and arousal--in determining choice. We then tested the predictive power of this model for two types of decisions involving images: preference based selections (Study 2) and risk-reward trade-offs (Study 3). In both cases, the model derived in Study 1 predicted choice and outperformed competing models drawn from well-established theoretical views. Finally, we showed that this model has ecological validity: It predicted choices between news articles on the basis of headlines (Study 4). These findings have implications for diverse fields, including neuroeconomics and judgment and decision making.