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This paper is in the following e-collection/theme issue:

Formative Evaluation of Digital Health Interventions (3634) Web-based and Mobile Health Interventions (4371) Mobile Health (mhealth) (3779) Obesity and Nutrition as Public Health Problem (457) Glucose Tracking and Self-Monitoring of Blood Glucose (214) Apps, Mobile, Wearables for Diabetes (393) Sensors for Glucose Monitoring and Diabetes Management (59) Instruments and Questionnaires for Nutrition and Food Intake (234) Design and Usability of Consumer Health Tech and Home Monitoring Devices (370) Innovations and Technology for Healthy Eating Education (519)

Published on in Vol 9 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/65368, first published .
Smartphone showing blood glucose reading of 5.3 mmol/L next to a glucose meter and breakfast

Real-World Effectiveness of Glucose-Guided Eating Using the Data-Driven Fasting App Among Adults Interested in Weight and Glucose Management: Observational Study

Real-World Effectiveness of Glucose-Guided Eating Using the Data-Driven Fasting App Among Adults Interested in Weight and Glucose Management: Observational Study

Authors of this article:

Michelle R Jospe1 Author Orcid Image ;   Martin Kendall2 Author Orcid Image ;   Susan M Schembre1 Author Orcid Image ;   Melyssa Roy3 Author Orcid Image
Article Authors Cited by (2) Tweetations (16) Metrics

Journals

  1. Jospe M, Richardson K, Schembre S. Continuous Glucose Monitoring for Personalized Nutrition in Real-World Vively App Users: Retrospective Observational Study. JMIR Human Factors 2026;13:e80734 View
  2. Mai A, Luan Y, Loy S, Qin C, Ji H, Obeng A, Oladuti M, Ejima K, Mok K, Kaur S, Huo C, Yang J, Ou Y, Khandpekar O, Yu X, Duah A, Ansu-Baidoo V, Bidulescu A, Abdalla M, Zoh R, Tekwe C. Reducing bias and enhancing equity in AI-enabled precision nutrition: addressing measurement error across wearables, multiomics, and dietary data. Frontiers in Digital Health 2026;8 View