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A web-based graphical food frequency assessment system:uddesign, development and usability metrics

机译:基于网络的图形化食物频率评估系统: ud设计,开发和可用性指标

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摘要

Background: Food frequency questionnaires (FFQs) are well established in the nutrition field, but there remain important questions around how to develop online tools in a way that can facilitate wider uptake. Also, FFQ user acceptance and evaluation have not been investigated extensively.ududObjective: This paper presents a Web-based graphical food frequency assessment system that addresses challenges of reproducibility, scalability, mobile friendliness,security, and usability and also presents the utilization metrics and user feedback from a deployment study.ududMethods: The application design employs a single-page application Web architecture with back-end services (database,authentication, and authorization) provided by Google Firebase’s free plan. Its design and responsiveness take advantage of the Bootstrap framework. The FFQ was deployed in Kuwait as part of the EatWellQ8 study during 2016. The EatWellQ8 FFQ contains 146 food items (including drinks). Participants were recruited in Kuwait without financial incentive. Completion time was based on browser timestamps and usability was measured using the System Usability Scale (SUS), scoring between 0 and 100. Products with a SUS higher than 70 are considered to be good.ududResults: A total of 235 participants created accounts in the system, and 163 completed the FFQ. Of those 163 participants, 142 reported their gender (93 female, 49 male) and 144 reported their date of birth (mean age of 35 years, range from 18-65 years). The mean completion time for all FFQs (n=163), excluding periods of interruption, was 14.2 minutes (95% CI 13.3-15.1 minutes). Female participants (n=93) completed in 14.1 minutes (95% CI 12.9-15.3 minutes) and male participants (n=49) completed in 14.3 minutes (95% CI 12.6-15.9 minutes). Participants using laptops or desktops (n=69) completed the FFQ in an average of 13.9 minutes (95% CI 12.6-15.1 minutes) and participants using smartphones or tablets (n=91) completed in an average of 14.5 minutes(95% CI 13.2-15.8 minutes). The median SUS score (n=141) was 75.0 (interquartile range [IQR] 12.5), and 84% of the participants who completed the SUS classified the system either “good” (n=50) or “excellent” (n=69). Considering only participants usingudsmartphones or tablets (n=80), the median score was 72.5(IQR 12.5), slightly below the SUS median for desktops and laptops(n=58), which was 75.0 (IQR 12.5). No significant differences were found between genders or age groups (below and above the median) for the SUS or completion time.ududConclusions: Taking into account all the requirements, the deployment used professional cloud computing at no cost, and the resulting system had good user acceptance. The results for smartphones/tablets were comparable with desktops/laptops. This work has potential to promote wider uptake of online tools that can assess dietary intake at scale.
机译:背景:食品频率调查表(FFQ)在营养领域已经建立,但在如何开发在线工具以促进更广泛的摄取方面仍然存在重要的问题。此外,FFQ用户的接受度和评估还没有得到广泛的研究。 ud ud目的:本文提出了一种基于Web的图形食物频率评估系统,该系统解决了可重复性,可扩展性,移动友好性,安全性和可用性方面的挑战,并提出了利用方法。指标和来自部署研究的用户反馈。 ud udMethods:应用程序设计采用了单页应用程序Web架构,并具有由Google Firebase的免费计划提供的后端服务(数据库,身份验证和授权)。它的设计和响应能力充分利用了Bootstrap框架。 FFQ作为2016年EatWellQ8研究的一部分在科威特进行了部署。EatWellQ8FFQ包含146种食品(包括饮料)。参加者在没有经济激励的情况下在科威特被招募。完成时间基于浏览器时间戳,使用系统可用性量表(SUS)评估可用性,评分在0到100之间。SUS高于70的产品被认为是不错。 ud ud结果:总共创建了235名参与者系统中的帐户,并且163完成了FFQ。在这163位参与者中,有142位报告了其性别(女性为93位,男性为49位),有144位报告了其出生日期(平均年龄为35岁,范围为18-65岁)。除中断期间外,所有FFQ的平均完成时间(n = 163)为14.2分钟(95%CI为13.3-15.1分钟)。女性参与者(n = 93)在14.1分钟内完成(95%CI 12.9-15.3分钟),男性参与者(n = 49)在14.3分钟内完成(95%CI 12.6-15.9分钟)。使用笔记本电脑或台式机的参与者(n = 69)平均完成FFQ 13.9分钟(95%CI 12.6-15.1分钟),使用智能手机或平板电脑的参与者(n = 91)平均完成14.5分钟(95%CI) 13.2-15.8分钟)。 SUS的中位数(n = 141)为75.0(四分位间距[IQR] 12.5),完成SUS的参与者中有84%将系统评为“好”(n = 50)或“优秀”(n = 69) )。仅考虑使用智能手机或平板电脑的参与者(n = 80),中位数为72.5(IQR 12.5),略低于台式机和笔记本电脑的SUS中位数(n = 58)(75.0(IQR 12.5))。在SUS或完成时间上,性别或年龄组(中位数以下和以下)之间没有发现显着差异。 ud ud结论:考虑到所有要求,部署免费使用了专业的云计算,并且所得到的系统具有良好的用户接受度。智能手机/平板电脑的结果与台式机/笔记本电脑相当。这项工作有可能促进在线工具的广泛使用,这些工​​具可以大规模评估饮食摄入量。

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