Keywords

Affective forecasting, impact bias, health belief model, nutrition, chronic disease states

Disciplines

Medicine and Health Sciences | Psychology

Mentor

Amanda Dillard

Abstract

Health outcomes are largely influenced by nutrition and diet choices, and many chronic disease states can be managed and prevented by optimizing diet. Nutritional intervention is a critical part of keeping high-risk patients from developing chronic disease, as well as minimizing symptoms of patients living with chronic disease. This is why patient adherence to dietary recommendations is so important, and why providers must understand how to promote patient behavior change when needed. When making decisions about health, people tend to fail to predict the intensity and duration of the emotions that will result from a given event or decision. Affective forecasting involves a person’s ability to predict their future emotions, and its impact bias error commonly accounts for overestimation of the intensity and duration of these emotions. This affective forecasting error could lead to patients make poor decisions about their health, including choosing not to comply with a specific diet to manage chronic disease. In order to combat this, it is essential for physicians to understand how to combat impact bias when introducing patients to new behavior change involving nutritional intervention. Providers need to be able to develop strategies to minimize affective forecasting error when patients are anticipating future emotions when told they need to change their behavior for their health. Research supports the idea that working to reduce focalism and adaptation neglect can decrease impact bias clouding patient decision-making. If physicians can implement strategies to achieve reduced impact bias, patients could potentially have increased adherence to diet intervention.

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Additional Files

Poster_Presentation.pdf (505 kB)
Affective Forecasting and Behavior in Nutrition Poster

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