Evidence map›Paper›PMID 36409539›Full record

Trial reportJournal of medical Internet research2022

Relative Validation of an Artificial Intelligence-Enhanced, Image-Assisted Mobile App for Dietary Assessment in Adults: Randomized Crossover Study.

Audrey Moyen, Aviva Ilysse Rappaport, Chloé Fleurent-Grégoire, Anne-Julie Tessier, Anne-Sophie Brazeau, Stéphanie Chevalier

Registry-linked trialOpen access · goldAbstract readRandomized Controlled Trial
In one paragraph

Trial report in Journal of medical Internet research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT07348432 (The diabEAT Study), which is not on this map. Cited by 20 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed, 1 pooled it
6.8field-weighted citation impact, top 2% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

NCT07348432 recruitingnot on this mapstarted 2024, after this paper: background citation

The diabEAT Study: Insulin dElivery Technologies And eaTing Behaviours in People With Type 1 Diabetes

TypeobservationalSponsorMcGill UniversityRan2024 to 2026Enrolled106ConditionsInsulin Dependent Diabetes Mellitus, Feeding and Eating Disorders, Eating Behavior, Type 1 DiabetesArmsAutomated Insulin Delivery (AID) Systems, Carbohydrate Counting Inaccuracy Percentage
3 · Its place in the literature

Who cites it

20 citing papers in PubMed, 1 synthesis or guideline pooled it, 37 citations in OpenAlex.

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  16. From Fetus to Eight: the CHILD Cohort Study.American journal of epidemiology · 2024
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors at 2 institutions in 1 country.

Audrey MoyenSchool of Human Nutrition, McGill University, Sainte-Anne-de-Bellevue, QC, Canada.ORCID 0000-0001-7156-3386
Aviva Ilysse RappaportSchool of Human Nutrition, McGill University, Sainte-Anne-de-Bellevue, QC, Canada.ORCID 0000-0002-2527-7909
Chloé Fleurent-GrégoireSchool of Human Nutrition, McGill University, Sainte-Anne-de-Bellevue, QC, Canada.ORCID 0000-0003-2970-6560
Anne-Julie TessierSchool of Human Nutrition, McGill University, Sainte-Anne-de-Bellevue, QC, Canada.ORCID 0000-0003-4551-1640
Anne-Sophie BrazeauSchool of Human Nutrition, McGill University, Sainte-Anne-de-Bellevue, QC, Canada.ORCID 0000-0002-2699-2920
Stéphanie ChevalierSchool of Human Nutrition, McGill University, Sainte-Anne-de-Bellevue, QC, Canada.ORCID 0000-0002-8497-1570
McGill University Health Centre · CAMcGill University · CA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThorough dietary assessment is essential to obtain accurate food and nutrient intake data yet challenging because of the limitations of current methods. Image-based methods may decrease energy underreporting and increase the validity of self-reported dietary intake. Keenoa is an image-assisted food diary that integrates artificial intelligence food recognition. We hypothesized that Keenoa is as valid for dietary assessment as the automated self-administered 24-hour recall (ASA24)-Canada and better appreciated by users.

objectiveWe aimed to evaluate the relative validity of Keenoa against a 24-hour validated web-based food recall platform (ASA24) in both healthy individuals and those living with diabetes. Secondary objectives were to compare the proportion of under- and overreporters between tools and to assess the user's appreciation of the tools.

methodsWe used a randomized crossover design, and participants completed 4 days of Keenoa food tracking and 4 days of ASA24 food recalls. The System Usability Scale was used to assess perceived ease of use. Differences in reported intakes were analyzed using 2-tailed paired t tests or Wilcoxon signed-rank test and deattenuated correlations by Spearman coefficient. Agreement and bias were determined using the Bland-Altman test. Weighted Cohen κ was used for cross-classification analysis. Energy underreporting was defined as a ratio of reported energy intake to estimated resting energy expenditure <0.9.

resultsA total of 136 participants were included (mean 46.1, SD 14.6 years; 49/136, 36% men; 31/136, 22.8% with diabetes). The average reported energy intakes (kcal/d) were 2171 (SD 553) in men with Keenoa and 2118 (SD 566) in men with ASA24 (P=.38) and, in women, 1804 (SD 404) with Keenoa and 1784 (SD 389) with ASA24 (P=.61). The overall mean difference (kcal/d) was -32 (95% CI -97 to 33), with limits of agreement of -789 to 725, indicating acceptable agreement between tools without bias. Mean reported macronutrient, calcium, potassium, and folate intakes did not significantly differ between tools. Reported fiber and iron intakes were higher, and sodium intake lower, with Keenoa than ASA24. Intakes in all macronutrients (r=0.48-0.73) and micronutrients analyzed (r=0.40-0.74) were correlated (all P<.05) between tools. Weighted Cohen κ scores ranged from 0.30 to 0.52 (all P<.001). The underreporting rate was 8.8% (12/136) with both tools. Mean System Usability Scale scores were higher for Keenoa than ASA24 (77/100, 77% vs 53/100, 53%; P<.001); 74.8% (101/135) of participants preferred Keenoa.

conclusionsThe Keenoa app showed moderate to strong relative validity against ASA24 for energy, macronutrient, and most micronutrient intakes analyzed in healthy adults and those with diabetes. Keenoa is a new, alternative tool that may facilitate the work of dietitians and nutrition researchers. The perceived ease of use may improve food-tracking adherence over longer periods.

Indexed as

Artificial IntelligenceMobile ApplicationsAdultCross-Over StudiesDietary FiberFemaleHumansMaleNutrition AssessmentDietary FiberASA24automated self-administered 24-hour recalldietary assessmentdietary intakefood diaryfood recordsKeenoa

Identifiers

PMID36409539
PMCPMC9723975
OpenAlexW4309657883

What OpenQuestion holds

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LicenceCC BY
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Registered trials

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.