Evaluation of PIQNIQ, a Novel Mobile Application for Capturing Dietary Intake

Caroline M Blanchard, Meghan K Chin, Cheryl H Gilhooly, Kathryn Barger, Gregory Matuszek, Akari J Miki, Richard G Côté, Alison L Eldridge, Hilary Green, Fabio Mainardi, Damian Mehers, Frédéric Ronga, Vera Steullet, Sai Krupa Das, Caroline M Blanchard, Meghan K Chin, Cheryl H Gilhooly, Kathryn Barger, Gregory Matuszek, Akari J Miki, Richard G Côté, Alison L Eldridge, Hilary Green, Fabio Mainardi, Damian Mehers, Frédéric Ronga, Vera Steullet, Sai Krupa Das

Abstract

Background: Accurate measurement of dietary intake is vital for providing nutrition interventions and understanding the complex role of diet in health. Traditional dietary assessment methods are very resource intensive and burdensome to participants. Technology may help mitigate these limitations and improve dietary data capture.

Objective: Our objective was to evaluate the accuracy of a novel mobile application (PIQNIQ) in capturing dietary intake by self-report. Our secondary objective was to assess whether food capture using PIQNIQ was comparable with an interviewer-assisted 24-h recall (24HR).

Methods: This study was a single-center randomized clinical trial enrolling 132 adults aged 18 to 65 y from the general population. Under a provided-food protocol with 3 menus designed to include a variety of foods, participants were randomly assigned to 1 of 3 food capture methods: simultaneous entry using PIQNIQ, photo-assisted recall using PIQNIQ, and 24HR. Primary outcomes were energy and nutrient content (calories, total fat, carbohydrates, protein, added sugars, calcium, dietary fiber, folate, iron, magnesium, potassium, saturated fat, sodium, and vitamins A, C, D, and E) captured by the 3 methods.

Results: The majority of nutrients reported were within 30% of consumed intake in all 3 food capture methods (n = 129 completers). Reported intake was highly (>30%) overestimated for added sugars in both PIQNIQ groups and underestimated for calcium in the photo-assisted recall group only (P < 0.001 for all). However, in general, both PIQNIQ methods had similar levels of accuracy and were comparable to the 24HR except in their overestimation (>30%) of added sugars and total fat (P < 0.001 for both).

Conclusions: Our results suggest that intuitive, technology-based methods of dietary data capture are well suited to modern users and, with proper execution, can provide data that are comparable to data obtained with traditional methods. This trial was registered at clinicaltrials.gov as NCT03578458.

Keywords: adult; dietary intake assessment; humans; mobile applications; nutrients; self-report.

© The Author(s) 2021. Published by Oxford University Press on behalf of the American Society for Nutrition.

Figures

FIGURE 1
FIGURE 1
Study visits for each menu cycle based on assigned food capture method. Day 1 procedures were completed on site for breakfast and off site for all other eating occasions; Day 2 procedures were completed on site only. This cycle was completed for each of the 3 menus; the participant's food capture method remained consistent across menus, and menus could not be completed on consecutive days.
FIGURE 2
FIGURE 2
Logging an apple in PIQNIQ. (A) By choosing to add a food item for breakfast on PIQNIQ's diary screen (not shown), the user initiates a text search. (B) The user types the desired food item (“apple”), which automatically populates a list of related items (“apple,” “apple pie,” “apple cake”). (C) By choosing “apple,” the user is brought to the portion size selection screen, with the visual portion size selector as the default option. The slider to the right of the image can be moved up or down to increase or decrease portion size, and the amount of apple on the plate will change accordingly. By tilting the phone backward and forward, the user can change his viewing angle of the food item and place setting. (D) If the user does not wish to use the portion size selector, he can toggle to manual entry by tapping the switch labeled “Select portion and quantity manually.” In this example, the user selects his desired unit (small; 2¾″ in diameter) from a dropdown menu and enters the item's value (“1”) using text entry. The available units vary by food item.

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