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Validity and Usability of a Smartphone Image-Based Dietary Assessment App Compared to 3-Day Food Diaries in Assessing Dietary Intake Among Canadian Adults: Randomized Controlled Trial

机译:基于智能手机的饮食评估应用程序的有效性和可用性与3天的饮食日记相比评估加拿大成人膳食摄入量:随机对照试验

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Background Accurate dietary assessment is needed in studies that include analysis of nutritional intake. Image-based dietary assessment apps have gained in popularity for assessing diet, which may ease researcher and participant burden compared to traditional pen-to-paper methods. However, few studies report the validity of these apps for use in research. Keenoa is a smartphone image-based dietary assessment app that recognizes and identifies food items using artificial intelligence and permits real-time editing of food journals. Objective This study aimed to assess the relative validity of an image-based dietary assessment app — Keenoa — against a 3-day food diary (3DFD) and to test its usability in a sample of healthy Canadian adults. Methods We recruited 102 participants to complete two 3-day food records. For 2 weeks, on 2 non-consecutive days and 1 weekend day, in random order, participants completed a traditional pen-to-paper 3DFD and the Keenoa app. At the end of the study, participants completed the System Usability Scale. The nutrient analyses of the 3DFD and Keenoa data before (Keenoa-participant) and after they were reviewed by dietitians (Keenoa-dietitian) were analyzed using analysis of variance. Multiple tests, including the Pearson coefficient, cross-classification, kappa score, % difference, paired t test, and Bland-Altman test, were performed to analyze the validity of Keenoa (Keenoa-dietitian). Results The study was completed by 72 subjects. Most variables were significantly different between Keenoa-participant and Keenoa-dietitian ( P .05) except for energy, protein, carbohydrates, fiber, vitamin B1, vitamin B12, vitamin C, vitamin D, and potassium. Significant differences in total energy, protein, carbohydrates, % fat, saturated fatty acids, iron, and potassium were found between the 3DFD and Keenoa-dietitian data ( P .05). The Pearson correlation coefficients between the Keenoa-dietitian and 3DFD ranged from .04 to .51. Differences between the mean intakes assessed by the 3DFD and Keenoa-dietitian were within 10% except for vitamin D (misclassification rate=33.8%). The majority of nutrients were within an acceptable range of agreement in the Bland-Altman analysis; no agreements were seen for total energy, protein, carbohydrates, fat (%), saturated fatty acids, iron, potassium, and sodium ( P .05). According to the System Usability Scale, 34.2% of the participants preferred using Keenoa, while 9.6% preferred the 3DFD. Conclusions The Keenoa app provides acceptable relative validity for some nutrients compared to the 3DFD. However, the average intake of some nutrients, including energy, protein, carbohydrates, % fat, saturated fatty acids, and iron, differed from the average obtained using the 3DFD. These findings highlight the importance of verifying data entries of participants before proceeding with nutrient analysis. Overall, Keenoa showed better validity at the group level than the individual level, suggesting it can be used when focusing on the dietary intake of the general population. Further research is recommended with larger sample sizes and objective dietary assessment approaches.
机译:背景技术在研究中包括分析营养摄入量的研究需要准确的饮食评估。基于图像的饮食评估应用程序获得了评估饮食的普及,这可能缓解与传统笔对纸方法相比的研究人员和参与者负担。但是,很少有研究报告了这些应用在研究中使用的有效性。 Keenoa是一款基于智能手机的饮食评估应用程序,识别和识别使用人工智能的食品,并允许实时编辑食品期刊。目的本研究旨在评估基于图像的饮食评估App - Keenoa的相对有效性 - 针对3天的食物日记(3DFD),并在健康加拿大成年人的样本中测试其可用性。方法我们招募了102名参与者完成了两名3天的食物记录。 2周,在2个非连续日期和周末日,随机订单,参与者完成了传统的笔对3DFD和Keenoa应用程序。在研究结束时,参与者完成了系统可用性规模。使用差异分析分析了3DFD和Keenoa数据(Keenoa-Particant)之前和Keenoa数据的营养分析(Keenoa-extantant)和营养仪(Keenoa-entitian)进行分析。多次测试,包括Pearson系数,跨分类,κ评分,%差异,配对T测试和Bland-Altman测试,以分析Keenoa(Keenoa-entitian)的有效性。结果该研究由72个科目完成。除了能量,蛋白质,碳水化合物,纤维,维生素B1,维生素B12,维生素C,维生素D和钾外,大多数变量有显着差异。在3DFD和Keenoa-intitian数据之间发现总能量,蛋白质,碳水化合物,%脂肪,饱和脂肪酸,铁和钾的显着差异(P <.05)。 Keenoa-intiTian和3DFD之间的Pearson相关系数范围从.04到.51。 3DFD和Keenoa-entitian评估的平均摄入量之间的差异在10%以内,除了维生素D(错误分类率= 33.8%)。大多数营养素是在Bland-Altman分析中可接受的协议范围内;对于总能量,蛋白质,碳水化合物,脂肪(%),饱和脂肪酸,铁,钾和钠(P <.05)没有任何协议。根据系统可用性规模,34.2%的参与者使用Keenoa优选,而9.6%首选3DFD。结论与3DFD相比,Keenoa应用程序为某些营养素提供可接受的相对有效性。然而,一些营养素的平均摄入量,包括能量,蛋白质,碳水化合物,%脂肪,饱和脂肪酸和铁,与使用3DFD获得的平均值不同。这些发现突出了在进行营养分析之前验证参与者的数据条目的重要性。总体而言,Keenoa在组水平上显示了比个人级别更好的有效性,这表明它可以在专注于一般人群的饮食摄入量时使用。建议使用更大的样本尺寸和客观饮食评估方法进行进一步研究。

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