School of Psychological Science, University of Western, Australia; ARC Centre of Excellence in Cognition and Its Disorders, Australia.
School of Psychological Science, University of Western, Australia; ARC Centre of Excellence in Cognition and Its Disorders, Australia.
Appetite. 2019 Aug 1;139:189-196. doi: 10.1016/j.appet.2019.04.017. Epub 2019 Apr 26.
Calorie intake plays an important role in maintaining a healthy weight. As such, researchers often use the calorie content of food as a distinction when investigating appetite related brain processes and eating behaviour. This distinction assumes that observers accurately perceive caloric content. However, there is evidence suggesting this is not always the case. The current study examined how accurately observers could estimate the caloric content of food images from the widely used "Food-pics" database. Eight hundred and forty psychology undergraduate students (aged 16-60, 64% female) estimated the caloric value of 178 high and 182 low calorie foods. Calorie content of food from both categories was significantly overestimated. Additionally, 7.7% of low calorie images were misperceived as being high calorie images and 35% of high calorie images were misperceived as being low calorie foods. Neither participants' gender, nor the recognisability and likability of the food images, influenced calorie estimation. Our findings show that most people are unable to accurately estimate caloric content of most food. Despite this, a selection of food images were judged accurately, and we advocate the use of these in research where it is important to have low- and high-calorie food images. Specifically, we propose an optimised stimulus set of 25 high and 25 low calorie food images that are accurately judged by adult participants. In addition, we provide the open source dataset of our ratings of Food-pics images which, when added to the existing Food-pics attributes, creates an enhanced tool for researchers selecting food stimuli.
热量摄入在维持健康体重方面起着重要作用。因此，研究人员在研究与食欲相关的大脑过程和进食行为时，通常会将食物的热量含量作为区分标准。这种区分假设观察者能准确感知卡路里含量。然而，有证据表明情况并非总是如此。本研究检查了观察者在从广泛使用的“Food-pics”数据库中，能多准确地估计食物图像的卡路里含量。840 名心理学本科生（年龄 16-60 岁，64%为女性）估计了 178 种高卡路里和 182 种低卡路里食物的卡路里值。两类食物的卡路里含量都被明显高估了。此外，7.7%的低卡路里图像被错误地认为是高卡路里图像，35%的高卡路里图像被错误地认为是低卡路里食物。参与者的性别，以及食物图像的可识别性和可喜欢性，都没有影响卡路里的估计。我们的研究结果表明，大多数人无法准确估计大多数食物的卡路里含量。尽管如此，仍有一些食物图像被判断得很准确，我们提倡在需要低卡路里和高卡路里食物图像的研究中使用这些图像。具体来说，我们提出了一个由 25 种高卡路里和 25 种低卡路里食物图像组成的优化刺激集，这些图像被成年参与者准确判断。此外，我们提供了我们对 Food-pics 图像评分的开源数据集，该数据集与现有的 Food-pics 属性相结合，为研究人员选择食物刺激物提供了一个增强的工具。
