Evidence map›Paper›PMID 42035119›Full record

ArticleThe international journal of behavioral nutrition and physical activity2026

Development and usability of a mobile ecological momentary assessment platform for dietary surveillance in the U.S.

Susan M Schembre, Michelle R Jospe, Rick Weiss, Christopher A Taylor, Edward J Bedrick, Jessie Somerville, Julia Felrice, Kelli M Richardson, Genevieve F Dunton, Cynthia A Thomson

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Article in The international journal of behavioral nutrition and physical activity, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

Who cites it

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No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

10 authors.

Susan M SchembreDepartment of Oncology, Lombardi Comprehensive Cancer Center, Georgetown University, 2115 Wisconsin Avenue NW Suite 300, Washington, DC, 20007, USA. ss4731@georgetown.edu.
Michelle R JospeDepartment of Oncology, Lombardi Comprehensive Cancer Center, Georgetown University, 2115 Wisconsin Avenue NW Suite 300, Washington, DC, 20007, USA.
Rick WeissViocare, Inc., Princeton, NJ, 08542, USA.
Christopher A TaylorDivision of Medical Dietetics, The Ohio State University, Columbus, OH, 43210, USA.
Edward J BedrickDepartment of Epidemiology and Biostatistics, Mel and Enid Zuckerman College of Public Health, University of Arizona, Tucson, AZ, 85724, USA.
Jessie SomervilleDepartment of Oncology, Lombardi Comprehensive Cancer Center, Georgetown University, 2115 Wisconsin Avenue NW Suite 300, Washington, DC, 20007, USA.
Julia FelriceDepartment of Oncology, Lombardi Comprehensive Cancer Center, Georgetown University, 2115 Wisconsin Avenue NW Suite 300, Washington, DC, 20007, USA.
Kelli M RichardsonDepartment of Oncology, Lombardi Comprehensive Cancer Center, Georgetown University, 2115 Wisconsin Avenue NW Suite 300, Washington, DC, 20007, USA.
Genevieve F DuntonDepartment of Population and Public Health Sciences, University of Southern California, Los Angeles, CA, 90039, USA.
Cynthia A ThomsonDepartment of Health Promotion Sciences, Mel and Enid Zuckerman College of Public Health, University of Arizona, Tucson, AZ, 85724, USA.

Funding

Mobile Ecological Momentary Diet Assessment: A Low Burden, Ecologically-Valid Approach to Measuring Dietary Intake in Near-Real TimeR01CA244404 · NCI · UNIVERSITY OF ARIZONA · PI SCHEMBRE, SUSAN · 2021 to 2025
$3.3M
NCI NIH HHS R01 CA244404NCI NIH HHS R01CA244404
6 · The paper itself

Abstract

backgroundDietary surveillance is critical for addressing diet-related chronic diseases, yet traditional methods like 24-hour dietary recalls and food frequency questionnaires suffer from recall bias, high respondent burden, and inaccurate portion size estimation. Mobile ecological momentary dietary assessment (mEMDA) enables real-time dietary capture, reducing memory load and minimizing reactivity. This study describes the user-centered development and iterative usability testing of Edna, a research-quality mEMDA platform for large-scale, low-burden dietary surveillance. Edna integrates real-time self-report with an image-supported, demographically inclusive food list derived from NHANES data and automated linkage to USDA nutrient databases. Here, we describe Edna’s development and usability in diverse U.S. adults.

methodsThree sequential rounds of iterative, user-centered development and usability testing were conducted between June 2024 and June 2025. Participants (N = 146 U.S. adults, ages 19–65 years) were recruited nationally through recruited nationally through an online research volunteer registry using stratified sampling by age, sex, BMI, and geographic region. Participants were randomly assigned to event-contingent or interval-contingent sampling conditions and asked to log all dietary intake for 14 consecutive days. Development refinements were guided by quantitative usability metrics and structured participant feedback through daily surveys and end-of-study questionnaires between rounds. Primary outcomes included System Usability Scale (SUS) scores, percentage of days with logged entries (engagement), and interval completion (interval-contingent only). The app was iteratively refined between rounds based on user feedback until SUS scores plateaued (change < 3 points). Statistical analyses included independent samples t-tests and ANOVA.

resultsSUS scores increased from 71.7 (SD = 23.0) in Round 1 to 78.8 (SD = 19.3) in Round 3, exceeding the digital health app benchmark of 68. Engagement ranged from 92.5 to 97.6% of study days, and interval completion among interval-contingent users ranged from 76 to 87%. Participants rated portion-size images as clear and culturally inclusive, with 94% reporting excellent overall experience.

conclusionsEdna achieved above-average usability and engagement, demonstrating that mEMDA is acceptable for population-level dietary surveillance. These findings support integration of EMA-based tools into routine public health nutrition monitoring to capture dietary behaviors more dynamically with reduced burden compared to traditional assessment methods.

Indexed as

DietEcological Momentary AssessmentMobile ApplicationsNutrition AssessmentAdultAgedFemaleHumansMaleMiddle AgedNutrition SurveysSelf ReportUnited StatesYoung AdultDietary measurementDietary surveillanceEcological momentary assessmentMobile healthUsability testingUser-centered design

Identifiers

PMID42035119
PMCPMC13251139

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.