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

Methods and Feasibility Studies (747) mHealth for Data Collection and Research (1719) Wearable Devices and Sensors (1577) Instruments and Questionnaires for Nutrition and Food Intake (248) Datasets (36) Development and Evaluation of Research Methods, Instruments and Tools (1321) Digital Biomarkers and Digital Phenotyping (434) Ecological Momentary Assessment (EMA) (505) Data Science (701)

Published on in Vol 15 (2026)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/70186, first published .
Woman checks fitness tracker watch while sitting by laptop and salad

Standardized Methods for Evaluating Physical and Eating Behaviors: The WEALTH Cross-Sectional Study Protocol

Standardized Methods for Evaluating Physical and Eating Behaviors: The WEALTH Cross-Sectional Study Protocol

Authors of this article:

Grainne Hayes1 Author Orcid Image ;   Christoph Buck2 Author Orcid Image ;   Greet Cardon3 Author Orcid Image ;   Richard Cimler4 Author Orcid Image ;   Steriani Elavsky5 Author Orcid Image ;   Leopold Fezeu K6 Author Orcid Image ;   Janas M Harrington7 Author Orcid Image ;   Jitka Kühnová4 Author Orcid Image ;   Jean-Michel Oppert6, 8 Author Orcid Image ;   Luis Sigcha1 Author Orcid Image ;   Pepijn Van de Ven9 Author Orcid Image ;   Tomas Vetrovsky4 Author Orcid Image ;   Catherine B Woods1 Author Orcid Image ;   Antje Hebestreit2 Author Orcid Image ;   Alan E Donnelly1 Author Orcid Image
Article Authors Cited by (4) Tweetations (2) Metrics

Journals

  1. Nguyen V, Jeong Y, Lee T. Identifying Individuals at Risk of Functional Decline Despite Preserved Muscle Mass: Insights from Appendicular Skeletal Muscle Mass and Handgrip Strength Discordance. Journal of Clinical Medicine 2026;15(7):2650 View
  2. Sigcha L, Swenne A, Hayes G, Kuhnova J, Cimler R, Elavsky S, Vetrovsky T, Fezeu Kamedjie L, Bouchan J, Oppert J, Harrington J, Cardon G, Hebestreit A, Donnelly A, Van de Ven P, Buck C. Robust Assessment of Free-Living Physical Behaviors and Activity Intensity Using Dual-Wearable Multitask Learning: Development and Evaluation Study From the Multicenter WEALTH Project. JMIR mHealth and uHealth 2026;14:e94302 View
  3. Neilson H, Asgari S, Tooze J, Khandwala F, Koushik A, Rabasa-Lhoret R, Kopciuk K, Csizmadi I. Leveraging questionnaire-based physical activity levels and the Goldberg method to evaluate the biological plausibility of self-reported energy intake: a doubly labeled water validation study. American Journal of Epidemiology 2026 View
  4. Kose J, Bouchan J, Fezeu L, Gauffeny N, Buck C, Cimler R, Donnelly A, Elavsky S, Harrington J, Hayes G, Hebestreit A, Sigcha L, Vetrovsky T, Cardon G, Oppert J. Behavioral and Contextual Patterns Derived From Ecological Momentary Assessment and Wearable Sensors and Their Associations With Health-Related Outcomes: WEALTH Cross-Sectional Study. JMIR Formative Research 2026;10:e85991 View