Lloyd E Caitlin, Shehzad Zarrar, Schebendach Janet, Bakkour Akram, Xue Alice M, Assaf Naomi Folasade, Jilani Rayman, Walsh B Timothy, Steinglass Joanna, Foerde Karin
Department of Psychiatry, Columbia University Irving Medical Center, New York, NY, United States.
New York State Psychiatric Institute, New York, NY, United States.
Front Psychol. 2020 Dec 23;11:585044. doi: 10.3389/fpsyg.2020.585044. eCollection 2020.
Food images are useful stimuli for the study of cognitive processes as well as eating behavior. To enhance rigor and reproducibility in task-based research, it is advantageous to have stimulus sets that are publicly available and well characterized. Food Folio by Columbia Center for Eating Disorders is a publicly available set of 138 images of Western food items. The set was developed for the study of eating disorders, particularly for use in tasks that capture eating behavior characteristic of these illnesses. It contains foods that are typically eaten, as well as those typically avoided, by individuals with eating disorders. Each image has now been rated across 17 different attributes by a large general United States population sample via Amazon's Mechanical Turk ( = 1054). Ratings included subjective attributes (e.g., tastiness, healthiness, and favorable texture) as well as estimates of nutrient content (e.g., fat and carbohydrate). Each participant rated a subset of stimulus set food items (46 foods) on all 17 dimensions. Additional description of the image set is provided in terms of physical image information and accurate nutritional information. Correlations between subjective ratings were calculated and an exploratory factor analysis and exploratory cluster analysis completed. Outcomes of the factor analysis suggested foods may be described along three latent factors of healthiness, tastiness, and umami taste; the cluster analysis highlighted five distinct clusters of foods varying on these same dimensions. Descriptive outcomes indicated that the stimulus set includes a range of foods that vary along multiple dimensions and thus is likely to be useful in addressing various research questions surrounding eating behavior and cognition in healthy populations, as well as in those with eating disorders. The provision of comprehensive descriptive information allows for stimulus selection that is optimized for a given research question and promotes strong inference.
食物图像是研究认知过程以及饮食行为的有用刺激物。为了提高基于任务的研究的严谨性和可重复性,拥有公开可用且特征明确的刺激集是有利的。哥伦比亚饮食失调中心的《食物档案》是一组公开可用的138张西方食物图像。该图像集是为饮食失调研究而开发的,特别是用于捕捉这些疾病典型饮食行为的任务。它包含饮食失调患者通常食用的食物以及通常避免食用的食物。现在,通过亚马逊的土耳其机器人( = 1054),美国大量普通人群样本对每张图像的17种不同属性进行了评分。评分包括主观属性(如美味、健康和良好质地)以及营养成分估计(如脂肪和碳水化合物)。每位参与者对刺激集食物项目的一个子集(46种食物)的所有17个维度进行了评分。根据物理图像信息和准确的营养信息提供了图像集的更多描述。计算了主观评分之间的相关性,并完成了探索性因素分析和探索性聚类分析。因素分析的结果表明,食物可以沿着健康、美味和鲜味这三个潜在因素来描述;聚类分析突出了在这些相同维度上变化的五个不同食物类别。描述性结果表明,该刺激集包括一系列在多个维度上变化的食物,因此可能有助于解决围绕健康人群以及饮食失调人群的饮食行为和认知的各种研究问题。提供全面的描述性信息允许针对给定的研究问题进行优化的刺激选择,并促进有力的推断。