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Citing this Article

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Published on 27.10.15 in Vol 3, No 4 (2015): Oct-Dec

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

Works citing "Electronic Dietary Intake Assessment (e-DIA): Comparison of a Mobile Phone Digital Entry App for Dietary Data Collection With 24-Hour Dietary Recalls"

According to Crossref, the following articles are citing this article (DOI 10.2196/mhealth.4613):

(note that this is only a small subset of citations)

  1. Chen J, Allman-Farinelli M. Impact of Training and Integration of Apps Into Dietetic Practice on Dietitians’ Self-Efficacy With Using Mobile Health Apps and Patient Satisfaction. JMIR mHealth and uHealth 2019;7(3):e12349
    CrossRef
  2. Ferreira LH, Smolarek AC, Chilibeck PD, Barros MP, McAnulty SR, Schoenfeld BJ, Zandona BA, Souza-Junior TP. High doses of sodium bicarbonate increase lactate levels and delay exhaustion in a cycling performance test. Nutrition 2019;60:94
    CrossRef
  3. Slavin M, Polasky A, Vieyra K, Best A, Durant L, Frankenfeld C. Single-Meal Nutrient Assessment by a Self-Administered, Electronic Exit Survey Compared with a Multipass Dietary Interview in University Undergraduates in an All-You-Care-to-Eat Campus Dining Hall. Journal of the Academy of Nutrition and Dietetics 2019;119(5):739
    CrossRef
  4. Wellard-Cole L, Chen J, Davies A, Wong A, Huynh S, Rangan A, Allman-Farinelli M. Relative Validity of the Eat and Track (EaT) Smartphone App for Collection of Dietary Intake Data in 18-to-30-Year Olds. Nutrients 2019;11(3):621
    CrossRef
  5. Fallaize R, Zenun Franco R, Pasang J, Hwang F, Lovegrove JA. Popular Nutrition-Related Mobile Apps: An Agreement Assessment Against a UK Reference Method. JMIR mHealth and uHealth 2019;7(2):e9838
    CrossRef
  6. Béjar LM, García-Perea MD, Reyes A, Vázquez-Limón E. Relative Validity of a Method Based on a Smartphone App (Electronic 12-Hour Dietary Recall) to Estimate Habitual Dietary Intake in Adults. JMIR mHealth and uHealth 2019;7(4):e11531
    CrossRef
  7. Chen J, Berkman W, Bardouh M, Ng CYK, Allman-Farinelli M. The use of a food logging app in the naturalistic setting fails to provide accurate measurements of nutrients and poses usability challenges. Nutrition 2019;57:208
    CrossRef
  8. Teixeira V, Voci SM, Mendes-Netto RS, da Silva DG. The relative validity of a food record using the smartphone application MyFitnessPal. Nutrition & Dietetics 2018;75(2):219
    CrossRef
  9. Wellard-Cole L, Jung J, Kay J, Rangan A, Chapman K, Watson WL, Hughes C, Ni Mhurchu C, Bauman A, Gemming L, Yacef K, Koprinska I, Allman-Farinelli M. Examining the Frequency and Contribution of Foods Eaten Away From Home in the Diets of 18- to 30-Year-Old Australians Using Smartphone Dietary Assessment (MYMeals): Protocol for a Cross-Sectional Study. JMIR Research Protocols 2018;7(1):e24
    CrossRef
  10. Fowler LA, Yingling LR, Brooks AT, Wallen GR, Peters-Lawrence M, McClurkin M, Wiley Jr KL, Mitchell VM, Johnson TD, Curry KE, Johnson AA, Graham AP, Graham LA, Powell-Wiley TM. Digital Food Records in Community-Based Interventions: Mixed-Methods Pilot Study. JMIR mHealth and uHealth 2018;6(7):e160
    CrossRef
  11. Griffiths C, Harnack L, Pereira MA. Assessment of the accuracy of nutrient calculations of five popular nutrition tracking applications. Public Health Nutrition 2018;21(8):1495
    CrossRef
  12. Béjar LM, Reyes A, García-Perea MD. Electronic 12-Hour Dietary Recall (e-12HR): Comparison of a Mobile Phone App for Dietary Intake Assessment With a Food Frequency Questionnaire and Four Dietary Records. JMIR mHealth and uHealth 2018;6(6):e10409
    CrossRef
  13. Jenner SL, Trakman G, Coutts A, Kempton T, Ryan S, Forsyth A, Belski R. Dietary intake of professional Australian football athletes surrounding body composition assessment. Journal of the International Society of Sports Nutrition 2018;15(1)
    CrossRef
  14. Eldridge A, Piernas C, Illner A, Gibney M, Gurinović M, de Vries J, Cade J. Evaluation of New Technology-Based Tools for Dietary Intake Assessment—An ILSI Europe Dietary Intake and Exposure Task Force Evaluation. Nutrients 2018;11(1):55
    CrossRef
  15. Chmurzynska A, Mlodzik-Czyzewska M, Malinowska A, Czarnocinska J, Wiebe D. Use of a Smartphone Application Can Improve Assessment of High-Fat Food Consumption in Overweight Individuals. Nutrients 2018;10(11):1692
    CrossRef
  16. Wellard-Cole L, Potter M, Jung J, Chen J, Kay J, Allman-Farinelli M. A Tool to Measure Young Adults’ Food Intake: Design and Development of an Australian Database of Foods for the Eat and Track Smartphone App. JMIR mHealth and uHealth 2018;6(11):e12136
    CrossRef
  17. Chen J, Gemming L, Hanning R, Allman-Farinelli M. Smartphone apps and the nutrition care process: Current perspectives and future considerations. Patient Education and Counseling 2018;101(4):750
    CrossRef
  18. Parr E, Devlin B, Callahan M, Radford B, Blankenship J, Dunstan D, Hawley J. Effects of Providing High-Fat versus High-Carbohydrate Meals on Daily and Postprandial Physical Activity and Glucose Patterns: a Randomised Controlled Trial. Nutrients 2018;10(5):557
    CrossRef
  19. Ambrosini GL, Hurworth M, Giglia R, Trapp G, Strauss P. Feasibility of a commercial smartphone application for dietary assessment in epidemiological research and comparison with 24-h dietary recalls. Nutrition Journal 2018;17(1)
    CrossRef
  20. Conrad J, Nöthlings U. Innovative approaches to estimate individual usual dietary intake in large-scale epidemiological studies. Proceedings of the Nutrition Society 2017;76(3):213
    CrossRef
  21. Ahmed M, Mandic I, Lou W, Goodman L, Jacobs I, L’Abbé M. Validation of a Tablet Application for Assessing Dietary Intakes Compared with the Measured Food Intake/Food Waste Method in Military Personnel Consuming Field Rations. Nutrients 2017;9(3):200
    CrossRef
  22. Allman-Farinelli M, Gemming L. Technology Interventions to Manage Food Intake: Where Are We Now?. Current Diabetes Reports 2017;17(11)
    CrossRef
  23. Béjar LM. First evaluation steps of a new method for dietary intake estimation regarding a list of key food groups in adults and in different sociodemographic and health-related behaviour strata. Public Health Nutrition 2017;20(15):2660
    CrossRef
  24. Chen J, Lieffers J, Bauman A, Hanning R, Allman-Farinelli M. Designing Health Apps to Support Dietetic Professional Practice and Their Patients: Qualitative Results From an International Survey. JMIR mHealth and uHealth 2017;5(3):e40
    CrossRef
  25. Pendergast FJ, Leech RM, McNaughton SA. Novel Online or Mobile Methods to Assess Eating Patterns. Current Nutrition Reports 2017;6(3):212
    CrossRef
  26. Roy R, Rangan A, Hebden L, Yu Louie JC, Tang LM, Kay J, Allman-Farinelli M. Dietary contribution of foods and beverages sold within a university campus and its effect on diet quality of young adults. Nutrition 2017;34:118
    CrossRef
  27. Pendergast FJ, Ridgers ND, Worsley A, McNaughton SA. Evaluation of a smartphone food diary application using objectively measured energy expenditure. International Journal of Behavioral Nutrition and Physical Activity 2017;14(1)
    CrossRef
  28. Rangan AM, Tieleman L, Louie JCY, Tang LM, Hebden L, Roy R, Kay J, Allman-Farinelli M. Electronic Dietary Intake Assessment (e-DIA): relative validity of a mobile phone application to measure intake of food groups. British Journal of Nutrition 2016;115(12):2219
    CrossRef
  29. Hurt RT, McClave SA. Nutritional Assessment in Primary Care. Medical Clinics of North America 2016;100(6):1169
    CrossRef
  30. Bejar LM, Sharp BN, García-Perea MD. The e-EPIDEMIOLOGY Mobile Phone App for Dietary Intake Assessment: Comparison with a Food Frequency Questionnaire. JMIR Research Protocols 2016;5(4):e208
    CrossRef