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基于计算机的饱腹感评估可预测部分大小选择和食物摄入量的行为测量。

Computer-based assessments of expected satiety predict behavioural measures of portion-size selection and food intake.

机构信息

Nutrition and Behaviour Unit, School of Experimental Psychology, University of Bristol, 12a Priory Road, Bristol BS8 1TU, UK.

出版信息

Appetite. 2012 Dec;59(3):933-8. doi: 10.1016/j.appet.2012.09.007. Epub 2012 Sep 16.

Abstract

Previously, expected satiety (ES) has been measured using software and two-dimensional pictures presented on a computer screen. In this context, ES is an excellent predictor of self-selected portions, when quantified using similar images and similar software. In the present study we sought to establish the veracity of ES as a predictor of behaviours associated with real foods. Participants (N=30) used computer software to assess their ES and ideal portion of three familiar foods. A real bowl of one food (pasta and sauce) was then presented and participants self-selected an ideal portion size. They then consumed the portion ad libitum. Additional measures of appetite, expected and actual liking, novelty, and reward, were also taken. Importantly, our screen-based measures of expected satiety and ideal portion size were both significantly related to intake (p<.05). By contrast, measures of liking were relatively poor predictors (p>.05). In addition, consistent with previous studies, the majority (90%) of participants engaged in plate cleaning. Of these, 29.6% consumed more when prompted by the experimenter. Together, these findings further validate the use of screen-based measures to explore determinants of portion-size selection and energy intake in humans.

摘要

先前,人们使用软件和在计算机屏幕上呈现的二维图片来测量预期饱腹感(ES)。在这种情况下,当使用类似的图片和类似的软件来量化时,ES 是自我选择份量的极好预测指标。在本研究中,我们试图确定 ES 作为与真实食物相关行为的预测指标的准确性。参与者(N=30)使用计算机软件评估他们对三种熟悉食物的 ES 和理想份量。然后,提供一碗真正的食物(意大利面和酱汁),参与者自行选择理想的份量。然后他们自由进食。还采取了其他食欲、预期和实际喜好、新颖性和奖励的措施。重要的是,我们基于屏幕的预期饱腹感和理想份量的测量值与摄入量显著相关(p<.05)。相比之下,喜好的测量值是相对较差的预测指标(p>.05)。此外,与先前的研究一致,大多数(90%)参与者都会吃光盘子里的食物。在这些参与者中,有 29.6%的人在受到实验者提示时会吃得更多。这些发现进一步验证了使用基于屏幕的测量来探索人类选择份量和能量摄入的决定因素的有效性。

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