Debiasing affective forecasting errors with targeted, but not representative, experience narratives

Objective: To determine whether representative experience narratives (describing a range of possible experiences) or targeted experience narratives (targeting the direction of forecasting bias) can reduce affective forecasting errors, or errors in predictions of experiences. Methods: In Study 1, participants (N = 366) were surveyed about their experiences with 10 common medical events. Those who had never experienced the event provided ratings of predicted discomfort and those who had experienced the event provided ratings of actual discomfort. Participants making predictions were randomly assigned to either the representative experience narrative condition or the control condition in which they made predictions without reading narratives. In Study 2, participants (N = 196) were again surveyed about their experiences with these 10 medical events, but participants making predictions were randomly assigned to either the targeted experience narrative condition or the control condition. Results: Affective forecasting errors were observed in both studies. These forecasting errors were reduced with the use of targeted experience narratives (Study 2) but not representative experience narratives (Study 1). Conclusion: Targeted, but not representative, narratives improved the accuracy of predicted discomfort. Practice implications: Public collections of patient experiences should favor stories that target affective forecasting biases over stories representing the range of possible experiences. (C) 2016 Elsevier Ireland Ltd. All rights reserved.