{'fraction_non_alphanumeric': 0.017097966728280962, 'fraction_numerical': 0.0, 'mean_word_length': 5.030640668523677, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Reconsidering the Impact of Affective Forecasting

In the article ‘‘Affective Forecasting and Its Implications for Medical Ethics,’’ Rhodes and Strain present current research documenting a psychological bias that affects our ability to correctly predict future emotional states. The bias they discuss is the wrongful estimation of the emotional impact of significant events. Research on affective forecasting by T.D. Wilson and D.T. Gilbert indicates that people tend to overestimate both the positive and negative impact of events. Rhodes and Strain correctly note that the conclusions derived from the research—that bad events do not seem to affect us as much as previously assumed—has applications for medicine. In a field where doctors are often faced with delivering bad news and offering treatments that will significantly alter the lives of their patients, information that bad events are not as emotionality deleterious as once thought is good news. I argue in agreement with the authors that the research on the impact bias could support an attitude change in terms of how doctors approach and communicate with their patients. It can contribute, also, to a change in attitude when doctors are faced with the grim task of telling patients that they have a chronic illness or that they are faced with making difficult decisions about their health. I disagree, however, that the predicted impact of the biases in emotional forecasting is as all-encompassing as the authors claim. In the next section, I consider the effects of biases in affective forecasting on policymakers. I assert that, although the research on the impact bias reveals misconceptions about what is needed for happiness, it does not provide guidelines for endorsing policies. In the third section, I consider how the bias affects doctors and patients differently. I argue that doctors are not affected by the bias in the same way as patients. In the fourth section, I argue against Rhodes and Strain and claim that affective forecasting does not diminish decisional capacity. I argue further that because the bias is incorrigible, paternalism will not help in restoring patient autonomy.