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1.
Can J Diet Pract Res ; 83(1): 25-29, 2022 03 01.
Article in English | MEDLINE | ID: mdl-34582258

ABSTRACT

Keenoa™ is a novel Canadian diet application (app) currently used by Canadian dietitians to collect diet-related data from clients. The goal of this study was to evaluate Keenoa™ based on user feedback and compare it to a conventional pen and paper method. One hundred and two participants were recruited and randomly assigned to record their diets using this application for 3 nonconsecutive days. Following this, participants were invited to complete an online "exit" survey. Seventy-two subjects responded, with 50 completing an open-ended question asking for general feedback about the app. Data were reviewed and 3 main themes emerged: strengths, challenges, and future recommendations. Strengths associated with the app consisted of picture recognition software, the additional commentary feature, and the overall pleasant data collection process. Challenges that were identified included inconsistencies with the barcode scanning features, the limited food database, time to enter food details, and software issues. Future recommendations included using a larger food database, pairing dietary intake with physical activity monitoring, and having accessible nutritional data. Despite these limitations, participants preferred using mobile apps to record diet compared with traditional written food diaries.


Subject(s)
Mobile Applications , Canada , Diet/methods , Diet Records , Humans , Smartphone
2.
JMIR Mhealth Uhealth ; 8(9): e16953, 2020 09 09.
Article in English | MEDLINE | ID: mdl-32902389

ABSTRACT

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.


Subject(s)
Mobile Applications , Nutrition Assessment , Adolescent , Adult , Artificial Intelligence , Canada , Diet Records , Eating , Energy Intake , Female , Humans , Male , Middle Aged , Reproducibility of Results , Smartphone , Surveys and Questionnaires , Young Adult
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