Saturday, September 2, 2017

Contrary to the hypothesis, predicted pleasure eating sweets was significantly lower than observed pleasure

Fallon, Matthew D., "The Role of Affective Forecasting and the Impact Bias in Nutritional Health Behaviors" (2017). Grand Valley State University, Masters Theses. 854. http://scholarworks.gvsu.edu/theses/854

Abstract: Previous literature on affective forecasting has studied its role in health decisions, but there is little research investigating affective forecasting in diet choices and eating behaviors. The present study collected affective forecasts from 43 college participants before eating an indulgent snack and then observed emotions immediately after eating the snack. We predicted that emotion predictions would be significantly stronger than observed emotions, in support of previous literature on the impact bias. We also predicted that optimism would predict a stronger impact bias and that extraversion and neuroticism would have a role in forecasts and observed emotions. Contrary to our hypothesis, predicted pleasure (M=2.12) was significantly lower than observed pleasure (M=2.34), F(1,42)=5.44, p=.025. Likewise, for participants who ate M&Ms rather than cookies or chips, participants had significantly higher observed positive emotion (M=1.95) than they had predicted (1.73), F(1,14)=5.78, p=.031. Trait optimism had significant interaction effects for positive affect, for each food chosen, such that as optimism increases, predicted affect increased more rapidly than observed affect. Neuroticism and extraversion were found to significantly influence predicted and observed positive affect, but had no effect on the accuracy of the affective forecasts. The present findings did not indicate the presence of an impact bias, but support previous affective forecasting literature in other aspects. These findings indicate that many of the phenomena in affective forecasting influence food forecasts. This holds implications for future research on affective forecasting in food choice and interventions targeting forecasting errors to improve diet.

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