Relative Validity of the Eat and Track (EaT) Smartphone App for Collection of Dietary Intake Data in 18-to-30-Year Olds

Abstract

(1) Background: Smartphone dietary assessment apps can be acceptable and valid data collection methods but have predominantly been validated in highly educated women, and none specifically measured eating-out habits in young adults. (2) Methods: Participants recorded their food and beverage consumption for three days using the Eat and Track (EaT) app, and intakes were compared with three dietitian-administered 24-h recall interviews matched to the same days as the reference method. Wilcoxon signed-rank or t-tests, correlation coefficients and Bland–Altman plots assessed agreement between the two methods for energy and percentage energy from nutrients (%E). (3) Results: One hundred and eighty nine of 216 participants (54% females, 60% resided in higher socioeconomic areas, 49% university-educated) completed the study. There were significant differences in median energy intake between methods (p < 0.001), but the EaT app had acceptable agreement for most nutrient densities at the group level. Correlation coefficients ranged from r = 0.56 (%E fat) to 0.82 (%E sugars), and between 85% and 94% of participants were cross-classified into the same or adjacent quartiles. Bland–Altman plots showed wide limits of agreement but no obvious biases for nutrient densities except carbohydrate in males. (4) Conclusions: The EaT app can be used to assess group nutrient densities in a general population of 18-to-30-year olds.

Relative Validity of MijnEetmeter: A Food Diary App for Self-Monitoring of Dietary Intake

“…In addition, in other studies, energy and total fat intake was underestimated by food diary apps in comparison to interviewer-assisted 24-h dietary recalls [ 16 , 17 , 18 , 19 ], though the differences were not always statistically significant [ 20 , 21 , 22 , 23 ]. Underestimation was generally smaller for protein intake and, to a lesser extent, carbohydrate intake [ 24 ].…”

Iterative Development of an Innovative Smartphone-Based Dietary Assessment Tool: Traqq

“…Balancing the required level of accuracy and user-friendliness posed the following main challenges in the development of the app related to decisions on 1) data entry (i.e., selecting the most accurate method for food identification and portion size quantification), 2) food composition data (i.e., selecting an accurate database and creating a fullfledged food list), 3) customization options (i.e., flexibility in food list, portion size quantification, and recipes), and 4) validation (i.e., against traditional methods and/or independent measures) 3 , 50 Alimentaire (e-CA) 5 , and Eat and Track (EaT) 6 .…”

“…NOTE: While performing the tasks, the expert informs the researcher about his/her thought process, i.e., by explaining the steps needed to be completed to fulfill the described task. 6. Conduct a brief follow-up to clarify ambiguities 32 , and provide the expert the opportunity for additional feedback.…”

Advancement in Dietary Assessment and Self-Monitoring Using Technology

“…An interesting collection of articles are presented which range from quantitative, qualitative, and mixed method evaluations of the use of applications for dietary self-monitoring. For quantitative evaluation, the relative validity of the eat and track (EaT) smartphone app for the collection of dietary intake data was explored in young adults aged 18 to 30 years [15]. This population group is often difficult to engage in dietary and lifestyle interventions despite their known weight gain trajectory to be higher than any other population group.…”