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Minimizing Memory Errors in Child Diet Assessment

最大限度地减少儿童饮食评估中的记忆错误

基本信息

批准号：
8737209
负责人：
Tom Baranowski
金额：
$ 14.25万
依托单位：
BAYLOR COLLEGE OF MEDICINE
依托单位国家：
美国
项目类别：
财政年份：
2013
资助国家：
美国
起止时间：
2013-09-18 至 2015-08-31
项目状态：
已结题

项目摘要

DESCRIPTION (provided by applicant): Sun ASA24-Kids Accurate assessment of dietary intake is important for 1) evaluating the outcome of dietary change interventions, 2) assessing the relationship between diet and health outcomes (e.g., obesity, metabolic syndrome), 3) identifying factors (e.g. environmental, psychosocial) influencing dietary intake which could be targeted in change programs, and 4) assessing diet changes over time (called surveillance). Our research revealed 35% of the foods children reported consuming the previous day were imaginary (called intrusions: observers did not see those foods consumed) and 15% were forgotten (called omissions: foods observers recorded, but were not reported by the children). This level of error needs to be minimized to enhance children's dietary intake assessment accuracy. Pictures of actual meals served, and after consumption, should minimize intrusions and omissions. Problems with the smart phone method of taking meal pictures for children, however, are it requires remembering to carry and use the smart phone correctly at the right time, even in social circumstances (e.g., with certain friends) when child reticence, even embarrassment, may minimize some children's willingness to draw that kind of attention to themselves. Dr. Mingui Sun (U Pittsburgh) has developed a multisensory unit, the e.button, attached to the shirt, which includes a camera, battery and storage to record pictures of everything in front of a child at 2 to 10 second intervals throughout the day. The Sun System requires a trained research assistant to identify the foods, and use of an on screen malleable wire mesh feature to estimate amounts consumed (taking about 10 min/day of images), which are in turn verified by a nutrition/dietetics professional (taking about five min/day of images). Limits of this system are that many foods are hard to recognize in a photo (e.g., poor lighting, odd angle, unusual food, unusual preparation or presentation of the food). Similar problems will occur with an automated system using pattern recognition to identify the foods. The child who consumed the foods, alternatively, should be able to recognize an image of the foods without much difficulty. The ASA24-Kids, adapted to children's abilities from the Automated Self-Administered 24 hour recall (ASA24) for adults, enables children to self-report what they consumed the previous day. Combining the Sun System with ASA24-Kids may permit recording children's dietary intake that minimizes the limitations of child's 24 hour memory by providing images of the foods consumed, yet allows child review of foods in the images. While the feasibility of using an automated image capture method for dietary assessment has been established among adults, parallel work has not been done among children. As a result, we propose creating Sun-ASA24-Kids, adapting it to child abilities, and validating it in a field study. The Sun-ASA24-Kids system could minimize two major sources of child reporting error, and unclear picture errors.

描述（由申请人提供）：Sun ASA 24-Kids准确评估饮食摄入量对于1）评估饮食改变干预的结果，2）评估饮食与健康结果之间的关系（例如，肥胖、代谢综合征），3）识别影响饮食摄入的因素（例如环境、社会心理），这些因素可以作为改变计划的目标，以及4）评估饮食随时间的变化（称为监测）。我们的研究显示，35%的儿童报告前一天吃的食物是想象的（称为入侵：观察者没有看到这些食物），15%被遗忘（称为遗漏：食物观察者记录，但没有被儿童报告）。需要将这种误差水平降至最低，以提高儿童膳食摄入量评估的准确性。实际用餐的照片，以及消费后，应尽量减少干扰和遗漏。然而，为儿童拍摄膳食照片的智能电话方法的问题在于，它需要记住在正确的时间正确地携带和使用智能电话，即使在社交环境中（例如，当孩子的沉默，甚至是尴尬，可能会减少一些孩子吸引这种注意力的意愿。Mingui Sun博士（U匹兹堡）开发了一种多感官单元，即电子按钮，附在衬衫上，其中包括摄像头，电池和存储设备，可以在一天中以2到10秒的间隔记录孩子面前的一切。太阳系统需要一名训练有素的研究助理来识别食物，并使用屏幕上的可延展金属丝网特征来估计消耗量（每天拍摄约10分钟的图像），这又由营养/饮食学专业人员验证（每天拍摄约5分钟的图像）。该系统的局限性在于许多食物难以在照片中识别（例如，光线不好、角度奇怪、食物不寻常、食物的准备或呈现不寻常）。使用模式识别来识别食物的自动化系统也会出现类似的问题。或者，食用这些食物的孩子应该能够毫不费力地识别食物的图像。ASA 24-Kids根据成人自动自助24小时回忆（ASA 24）的儿童能力进行了调整，使儿童能够自我报告前一天摄入的食物。将Sun系统与ASA 24-Kids组合可以允许记录儿童的饮食摄入，这通过提供所消耗的食物的图像来最小化儿童的24小时记忆的限制，但允许儿童在图像中回顾食物。虽然在成人中已经建立了使用自动图像捕获方法进行饮食评估的可行性，但尚未在儿童中进行平行工作。因此，我们建议创建Sun-ASA 24-Kids，使其适应儿童的能力，并在实地研究中验证它。 Sun-ASA 24-Kids系统可以最大限度地减少儿童报告错误和图像不清晰错误的两个主要来源。