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

mHealth for Data Collection and Research (955) Instruments and Questionnaires for Nutrition and Food Intake (166)

Published on in Vol 7, No 2 (2019): February

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/11463, first published .
EVIDENT Smartphone App, a New Method for the Dietary Record: Comparison With a Food Frequency Questionnaire

EVIDENT Smartphone App, a New Method for the Dietary Record: Comparison With a Food Frequency Questionnaire

EVIDENT Smartphone App, a New Method for the Dietary Record: Comparison With a Food Frequency Questionnaire

Authors of this article:

Jose I Recio-Rodriguez1, 2, 3, 4 Author Orcid Image ;   Carmela Rodriguez-Martin1, 2, 3 Author Orcid Image ;   Jesus Gonzalez-Sanchez1, 2, 3, 5 Author Orcid Image ;   Emiliano Rodriguez-Sanchez1, 2, 3 Author Orcid Image ;   Carme Martin-Borras6, 7 Author Orcid Image ;   Vicente Martínez-Vizcaino8 Author Orcid Image ;   Maria Soledad Arietaleanizbeaskoa9 Author Orcid Image ;   Olga Magdalena-Gonzalez10 Author Orcid Image ;   Carmen Fernandez-Alonso11 Author Orcid Image ;   Jose A Maderuelo-Fernandez1, 2, 3 Author Orcid Image ;   Manuel A Gomez-Marcos1, 2, 3, 12 Author Orcid Image ;   Luis Garcia-Ortiz1, 2, 3, 13 Author Orcid Image ;   EVIDENT Investigators14
Article Authors Cited by (27) Tweetations (1) Metrics

Journals

  1. Patino-Alonso M, Gómez Sánchez M, Gómez Sánchez L, Alonso-Domínguez R, Sánchez-Aguadero N, Sánchez Salgado B, Rodríguez Sánchez E, García Ortiz L, Gómez-Marcos M. Multivariate Analysis of Influence of Vitamin Intake on Vascular Function Parameters by Sex in the General Spanish Population: EVA Study. Nutrients 2020;12(3):643 View
  2. Garcia-Yu I, Garcia-Ortiz L, Gomez-Marcos M, Rodriguez-Sanchez E, Lugones-Sanchez C, Maderuelo-Fernandez J, Recio-Rodriguez J. Cocoa-rich chocolate and body composition in postmenopausal women: a randomised clinical trial. British Journal of Nutrition 2021;125(5):548 View
  3. Jung J, Wellard-Cole L, Cai C, Koprinska I, Yacef K, Allman-Farinelli M, Kay J. Foundations for Systematic Evaluation and Benchmarking of a Mobile Food Logger in a Large-scale Nutrition Study. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 2020;4(2):1 View
  4. Reber E, Gomes F, Vasiloglou M, Schuetz P, Stanga Z. Nutritional Risk Screening and Assessment. Journal of Clinical Medicine 2019;8(7):1065 View
  5. Rodríguez-Martín C, Garcia-Ortiz L, Rodriguez-Sanchez E, Martin-Cantera C, Soriano-Cano A, Arietaleanizbeaskoa M, Magdalena-Belio J, Menendez-Suarez M, Maderuelo-Fernandez J, Lugones-Sanchez C, Gómez-Marcos M, Recio-Rodríguez J. The Relationship of the Atlantic Diet with Cardiovascular Risk Factors and Markers of Arterial Stiffness in Adults without Cardiovascular Disease. Nutrients 2019;11(4):742 View
  6. Garcia-Yu I, Garcia-Ortiz L, Gomez-Marcos M, Rodriguez-Sanchez E, Agudo-Conde C, Gonzalez-Sanchez J, Maderuelo-Fernandez J, Recio-Rodriguez J. Effects of Cocoa-Rich Chocolate on Blood Pressure, Cardiovascular Risk Factors, and Arterial Stiffness in Postmenopausal Women: A Randomized Clinical Trial. Nutrients 2020;12(6):1758 View
  7. Garcia-Yu I, Garcia-Ortiz L, Gomez-Marcos M, Rodriguez-Sanchez E, Mora-Simon S, Maderuelo-Fernandez J, Recio-Rodriguez J. Effects of cocoa-rich chocolate on cognitive performance in postmenopausal women. A randomised clinical trial. Nutritional Neuroscience 2022;25(6):1147 View
  8. Gonzalez-Ramirez M, Cejudo-Lopez A, Lozano-Navarrete M, Salamero Sánchez-Gabriel E, Torres-Bengoa A, Segura-Balbuena M, Sanchez-Cordero M, Barroso-Vazquez M, Perez-Barba F, Troncoso A, Garcia-Parrilla M, Cerezo A. SAlBi educa: A promising, tailored nutrition app for promoting healthy eating habits (Preprint). JMIR Formative Research 2020 View
  9. Morgenstern J, Rosella L, Costa A, de Souza R, Anderson L. Perspective: Big Data and Machine Learning Could Help Advance Nutritional Epidemiology. Advances in Nutrition 2021;12(3):621 View
  10. Ocké M, Dinnissen C, Stafleu A, de Vries J, van Rossum C. Relative Validity of MijnEetmeter: A Food Diary App for Self-Monitoring of Dietary Intake. Nutrients 2021;13(4):1135 View
  11. Zhang L, Misir A, Boshuizen H, Ocké M. A Systematic Review and Meta-Analysis of Validation Studies Performed on Dietary Record Apps. Advances in Nutrition 2021;12(6):2321 View
  12. Scarry A, Rice J, O' Connor E, Tierney A. Does the use of mobile applications or mobile health technology improve diet quality in adults? A protocol for a systematic literature review. HRB Open Research 2022;5:1 View
  13. Su S, Larsen H, Cousijn J, Wiers R, Van Den Eijnden R. Problematic smartphone use and the quantity and quality of peer engagement among adolescents: A longitudinal study. Computers in Human Behavior 2022;126:107025 View
  14. König L, Van Emmenis M, Nurmi J, Kassavou A, Sutton S. Characteristics of smartphone-based dietary assessment tools: a systematic review. Health Psychology Review 2022;16(4):526 View
  15. Lara-Breitinger K, Lynch M, Kopecky S. Nutrition Intervention in Cardiac Rehabilitation. Journal of Cardiopulmonary Rehabilitation and Prevention 2021;41(6):383 View
  16. Ding Y, Wan X, Lu G, Huang H, Liang Y, Yu J, Chen C. The associations between smartphone addiction and self-esteem, self-control, and social support among Chinese adolescents: A meta-analysis. Frontiers in Psychology 2022;13 View
  17. Rezaeipour M, Apanasenko G, Banparvari M. Weight-Loss Parameters and Quality of Life in Obese Aged Women Using WATERinMOTION. Health Scope 2021;10(2) View
  18. Long Z, Huang S, Zhang J, Zhang D, Yin J, He C, Zhang Q, Xu H, He H, Sun H, Xie K. A Digital Smartphone-Based Self-administered Tool (R+ Dietitian) for Nutritional Risk Screening and Dietary Assessment in Hospitalized Patients With Cancer: Evaluation and Diagnostic Accuracy Study. JMIR Formative Research 2022;6(10):e40316 View
  19. Moyen A, Rappaport A, Fleurent-Grégoire C, Tessier A, Brazeau A, Chevalier S. Relative Validation of an Artificial Intelligence–Enhanced, Image-Assisted Mobile App for Dietary Assessment in Adults: Randomized Crossover Study. Journal of Medical Internet Research 2022;24(11):e40449 View
  20. Patino-Alonso C, Gómez-Sánchez M, Gómez-Sánchez L, Rodríguez-Sánchez E, Agudo-Conde C, García-Ortiz L, Gómez-Marcos M. Diagnosing Vascular Aging Based on Macro and Micronutrients Using Ensemble Machine Learning. Mathematics 2023;11(7):1645 View
  21. Khor B, Sumida K, Scholes-Robertson N, Chan M, Lambert K, Kramer H, Lui S, Wang A. Nutrition Education Models for Patients With Chronic Kidney Disease. Seminars in Nephrology 2023;43(2):151404 View
  22. Jung C, Kim Y, Kim H, Han S, Yoo T, Kang S, Park J. Effectiveness of a Smartphone Application for Dietary Sodium Intake Measurement. Nutrients 2023;15(16):3590 View
  23. Larke J, Chin E, Bouzid Y, Nguyen T, Vainberg Y, Lee D, Pirsiavash H, Smilowitz J, Lemay D. Surveying Nutrient Assessment with Photographs of Meals (SNAPMe): A Benchmark Dataset of Food Photos for Dietary Assessment. Nutrients 2023;15(23):4972 View
  24. TOJI C, SAITO Y, HIROTA N, NOTSU A, FUKUI M, SASAKI S, DATE C. Validity and Reproducibility of a Food Frequency Questionnaire for Dietary Assessment in Japanese People. Journal of Nutritional Science and Vitaminology 2024;70(2):106 View
  25. Finanger T, Melby K, Spigset O, Andreassen T, Lydersen S, Skråstad R. Relationship between alcohol intake based on daily smartphone-reported consumption and PEth concentrations in healthy volunteers. Alcohol and Alcoholism 2024;59(4) View

Books/Policy Documents

  1. Dhanapal A, Sylvia Subapriya M. , Subramaniam K, Appukutty M. Integrating AI in IoT Analytics on the Cloud for Healthcare Applications. View