Research on affective forecasting shows that people have a robust tendency to overestimate the intensity of future emotion. We hypothesized that (a) people can accurately predict the intensity of their feelings about events and (b) a procedural artifact contributes to people's tendency to overestimate the intensity of their feelings in general. People may misinterpret the forecasting question as asking how they will feel about a focal event, but they are later asked to report their feelings in general without reference to that event. In the current investigation, participants predicted and reported both their feelings in general and their feelings about an election outcome (Study 1) and an exam grade (Study 3). We also assessed how participants interpreted forecasting questions (Studies 2 and 4) and conducted a meta-analysis of affective forecasting research (Study 5). The results showed that participants accurately predicted the intensity of their feelings about events. They overestimated only when asked to predict how they would feel in general and later report their feelings without reference to the focal event. Most participants, however, misinterpreted requests to predict their feelings in general as asking how they would feel when they were thinking about the focal event. Clarifying the meaning of the forecasting question significantly reduced overestimation. These findings reveal that people have more sophisticated self-knowledge than is commonly portrayed in the affective forecasting literature. Overestimation of future emotion is partly due to a procedure in which people predict one thing but are later asked to report another.
The models used in the study of communication and health behavior have changed from those describing how to impose health actions on relatively passive respondents to models describing how respondents regulate their own health practices. We have traced the change from the fear-drive model, which described how fear induced change, to the parallel response model, which described how subjects processed information and generated coping responses to solve the problem posed by both the objective health threat and by their subjective fear. The data supporting this change showed that increasing fear led to more favorable attitudes but that fear alone was insufficient to create action: Specific action instructions had to be added to both high and low fear and both combinations produced the same level of health action. Neither the data nor the parallel model specified what subjects learned about the threat that made exposure to a high or low fear message necessary for behavior change. The parallel response model has been elaborated into a more complete systems model and new studies show how health threats are represented. They have found attributes such as IDENTITY (label and symptoms), CAUSES, TIME LINES or duration, and CONSEQUENCES, that set goals and criteria to generate and evaluate problem solving (coping) behavior. Suggestions are made for applying this more complete model to public health practice.
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