The impact bias, a form of which is the durability bias, in affective forecasting, is the tendency for people to overestimate the length or the intensity of future feeling states.
In other words, people seem to think that if disaster strikes it will take longer to recover emotionally than it actually does. Conversely, if a happy event occurs, people overestimate how long they will emotionally benefit from it.
Daniel Gilbert and Timothy Wilson first identified this bias, and proposed the name change to refer more broadly to all forms of emotional "impact", including durability as well as intensity, and the rate of ascension and descension, etc. Daniel Kahneman has also contributed research on this cognitive bias.
A possible explanation for the impact bias is given by the theory of cognitive dissonance: most times people are very good at reducing cognitive dissonance, but, since it happens unconsciously, do not know it. Another explanation is 'focalism', the tendency in affective forecasting to neglect the influence of other activities in minimizing one event's impact.
Other articles related to "impact bias, bias, impact":
... memory and the perceived importance of a future event increase impact bias, but only for some individuals ... cultures exhibit less susceptibility to both impact bias and focalism ... has also investigated motivational components of affective forecasting, suggesting that impact bias may be a result of an effort to motivate ourselves towards achieving goals ...
... coined the term "immune neglect" (or "immune bias") to describe a function of the psychological immune system ... future events, that people with better coping strategies should have a bigger impact bias, or a greater difference between their predicted and actual outcome ... coped with their emotions instead of avoiding them would have a greater impact bias when predicting how they’d feel if their team lost the game ...
... of error in affective forecasting across various populations and situations is the impact bias, which is the tendency to overestimate the emotional impact of a future event ... Impact bias, including impact and durability bias findings are both robust and reliable errors found in affective forecasting ... Impact bias has also been found in retroactive assessments of the past events ...
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