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

BACKGROUND: Dietary 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. METHODS: Three 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. RESULTS: SUS 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. CONCLUSIONS: Edna 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.