Determinants of quality, specificity, and stability of emotional episodic memories in a fine-dining context

International Journal of Gastronomy and Food Science(2022)

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摘要
For theoretical and practical reasons, it is of great interest to understand how accurate and persistent episodic memories of enjoyable experiences are formed and maintained, for example, in the context of gastronomy and other instances of experience design. Here, we investigated factors that might affect the quality (a measure of coherence) of immediate and long-term emotional episodic memories of individual dishes of a long and complex dinner in a fine-dining restaurant. We also assessed long-term recognition memory for pictures of the dishes. Intra-class correlations revealed good immediate emotional episodic memory, which remained stable over three months. Contributing factors to these kinds of memory were assessed with path modelling. The quality of emotional episodic memory was enhanced by the hedonic intensity of the most valued dishes during the meal and was impaired with the hedonic intensity of the least valued dishes. Enjoying the final dish positively affects emotional memory after the experience. Interestingly, when diners reported to have been distracted from the meal, presumably by communicating with their meal companions about the food, it had a positive effect on the long-term emotional episodic memory. Personality traits of the diners had no substantial impact on either type of memory. Alcohol intake during the meal modestly affected recognition memory but – interestingly – had no statistically significant effect on emotional episodic memory. Altogether, this study provides novel information about the main determinants of the precision and temporal stability of emotional episodic memory and nonemotional recognition memory for a meal. These findings contribute to the psychological foundations of designing memorable experiences in gastronomy and other areas.
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关键词
Meal experience,Utility parameters,Emotional episodic memory,Recognition memory,Path modelling
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