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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, 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
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  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. 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
  4. 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
  5. 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
  6. 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
  7. 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
  8. 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
  9. 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
  10. Griffiths C, Harnack L, Pereira MA. Assessment of the accuracy of nutrient calculations of five popular nutrition tracking applications. Public Health Nutrition 2018;21(08):1495
    CrossRef
  11. 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
  12. 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
  13. 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
  14. 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
  15. Pendergast FJ, Leech RM, McNaughton SA. Novel Online or Mobile Methods to Assess Eating Patterns. Current Nutrition Reports 2017;6(3):212
    CrossRef
  16. 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
  17. 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
  18. Allman-Farinelli M, Gemming L. Technology Interventions to Manage Food Intake: Where Are We Now?. Current Diabetes Reports 2017;17(11)
    CrossRef
  19. 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
  20. 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
  21. 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
  22. Hurt RT, McClave SA. Nutritional Assessment in Primary Care. Medical Clinics of North America 2016;100(6):1169
    CrossRef
  23. 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