Abstract
Eating disorder and obesity rates are increasing, and treatment efficacy for these conditions is poor. Here, I examined accuracy and predictors of calorie estimation performance, to evaluate whether stimulus choice and participant selection affects the measurement of processes underpinning eating behaviours. I demonstrated that despite overall poor calorie estimation accuracy, certain food images and participant factors (namely, dieting status, considering healthiness, calorie knowledge and BMI status) predicted better calorie estimation accuracy. Food image findings were applied to the investigation of automatic action tendencies, a paradigm dependent on veridical calorie perception. These findings provide practical guidance for researchers investigating eating behaviours.
Original language | English |
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Qualification | Doctor of Philosophy |
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Award date | 7 Dec 2020 |
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Publication status | Unpublished - 2020 |