Understanding and Improving Predictions about Future Feelings
People try to make decisions that will improve their lives and make them happy, and to do so, they rely on affective forecasts--predictions about how future outcomes will make them feel. The greater the emotional impact people expect a future outcome to have, the more effort and resources they invest in attaining or avoiding it. Understandably then, inaccuracy in affective forecasting has been identified as a major obstacle to making good decisions. Decades of research suggest that people are poor at predicting how they will feel and commonly overestimate the impact that future events will have on their emotions. Although the simplicity of this idea is intuitively attractive, recent studies have revealed that people are actually very good at forecasting some features of their emotional reaction. The proposed research will provide a more precise understanding of when and why people are biased in their predictions about future feelings and how bias affects the quality of decisions. The results will inform interventions designed to improve decision-making in applied domains including health, public policy, education, and economics. People making important decisions--such as whether to undergo surgery, listen to public health warnings, or pursue a specific career-- will be better informed if they can accurately predict how the outcomes of their decisions will make them feel. Thus, interventions that improve forecasting are critically important for helping people make informed choices with implications for the length and quality of their lives.
This investigation tests a new theoretical model that explains past inconsistent results demonstrating that sometimes people overestimate, sometimes underestimate, and are sometimes accurate in their forecasts. The investigation clearly differentiates forecasts of emotional intensity, frequency, and duration for the first time both in laboratory and real-world settings. By allowing researchers to achieve greater precision about the features of emotion being predicted, these studies clarify when and why people overestimate, underestimate, and accurately predict their emotional reactions. The studies also analyze the differing causes of bias when people predict distinct features of emotion, the features of emotion that people spontaneously consider when making decisions in their daily lives, and the consequences of forecasting biases for decision quality. Addressing these questions is essential, not only for a theoretical understanding of how people think about their futures, but also for understanding how to intervene to improve decisions.
*This is a collaborative project with Linda J. Levine, and is funded by the National Science Foundation (#1451297)