This article relies largely or entirely on a single source. (May 2016)
In the psychology of affective forecasting, the impact bias, a form of which is the durability bias, is the tendency for people to overestimate the length or the intensity of future emotional states.
In Gilbert et al., 1998, there was a conducted study on individuals participating in a job interview. The participants were separated into two groups; the unfair decision condition (where the decision of being hired was left up to a single MBA student with sole authority listening to the interview) and the fair decision condition (where the decision was made by a team of MBA students who had to independently and unanimously decide the fate of the interviewee). Then, certain participants were chosen to forecast how they would feel if they were chosen or not chosen for the job immediately after learning if they had been hired or fired and then they had to predict how they would feel ten minutes after hearing the news. Then following the interview, all participants were given letters notifying them they had not been selected for the job. All participants were then required to fill out a questionnaire that reported their current happiness. Then after waiting ten minutes, the experimenter presented all the participants with another questionnaire that once again asked them to report their current level of happiness. The predictions made by the participants in both the unfair and fair groups were about the same regarding how they would feel immediately after hearing the news as well as ten minutes later. Both groups accurately predicted how they would feel immediately after hearing the news. The study showed that both groups felt much better than they had originally predicted, ten minutes later, demonstrating the impact bias.
Explanations for the occurrence of the impact bias include the following:
Misconstrual of future events: When predicting how an experience will impact us emotionally, events which have not been experienced are particularly difficult. Often how we think an event may be like does not relate to how the experience is like.
Inaccurate theories: People have created cultural theories and had experiences that greatly influence beliefs of how an event will affect us. For example, our culture has emphasized a correlation between wealth and happiness, however despite this belief; money does not necessarily bring happiness.
Motivated Distortions: When faced with a negative event people may have forecasts that are overestimated and can evoke either comfort or fear in the present. The overestimation however can often be used to soften the effects of an event or make it easier by the reality not being as extreme as the forecasted impact.
Under correction (anchoring and adjustment): People anchor their prediction on how they currently feel and never accurately adjust their prediction
Focalism: Often when making a prediction of the impact of an event people focus solely on the event in question. This ignores the fact that with the passage of time, other events will occur that influence happiness.
Immune Neglect: We have unconscious psychological processes such as ego defense, dissonance reductions, self-serving biases, etc. that will cushion the effects of a negative event.
Development in children
- Gilbert, Daniel T.; Pinel, Elizabeth C.; Wilson, Timothy D.; Blumberg, Stephen J.; Wheatley, Thalia P. (1998). "Immune neglect: A source of durability bias in affective forecasting" (PDF). Journal of Personality and Social Psychology. 75 (3): 617–638. doi:10.1037/0022-35184.108.40.2067. PMID 9781405. Archived from the original on 2016-05-17.
- "Affective forecasting bias in preschool children". Journal of Experimental Child Psychology. 159: 175–184. 2017-07-01. doi:10.1016/j.jecp.2017.02.005. ISSN 0022-0965.
- Kopp, Leia; Atance, Cristina M.; Pearce, Sean (2017-09-13). "'Things aren't so bad!': Preschoolers overpredict the emotional intensity of negative outcomes". British Journal of Developmental Psychology. 35 (4): 623–627. doi:10.1111/bjdp.12210. ISSN 0261-510X.