Published on in Vol 8, No 4 (2020): April

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/14726, first published .
Impact of a Mobile Phone App to Increase Vegetable Consumption and Variety in Adults: Large-Scale Community Cohort Study

Impact of a Mobile Phone App to Increase Vegetable Consumption and Variety in Adults: Large-Scale Community Cohort Study

Impact of a Mobile Phone App to Increase Vegetable Consumption and Variety in Adults: Large-Scale Community Cohort Study

Journals

  1. Mukaneeva D, Kontsevaya A, Karamnova N, Drapkina O. Population prevention measures aimed at increasing the consumption of vegetables and fruits: international experience and prospects for implementation in the Russian Federation. Profilakticheskaya meditsina 2020;23(6):129 View
  2. Hendrie G, Lyle G, Mauch C, Haddad J, Golley R. Understanding the Variation within a Dietary Guideline Index Score to Identify the Priority Food Group Targets for Improving Diet Quality across Population Subgroups. International Journal of Environmental Research and Public Health 2021;18(2):378 View
  3. Jakob R, Harperink S, Rudolf A, Fleisch E, Haug S, Mair J, Salamanca-Sanabria A, Kowatsch T. Factors Influencing Adherence to mHealth Apps for Prevention or Management of Noncommunicable Diseases: Systematic Review. Journal of Medical Internet Research 2022;24(5):e35371 View
  4. Lugones-Sánchez C, Recio-Rodríguez J, Menéndez-Suárez M, Saz-Lara A, Ramirez-Manent J, Sánchez-Calavera M, Gómez-Sánchez L, Rodríguez-Sánchez E, García-Ortiz L. Effect of a Multicomponent mHealth Intervention on the Composition of Diet in a Population with Overweight and Obesity—Randomized Clinical Trial EVIDENT 3. Nutrients 2022;14(2):270 View
  5. Livingstone K, Rawstorn J, Partridge S, Godrich S, McNaughton S, Hendrie G, Blekkenhorst L, Maddison R, Zhang Y, Barnett S, Mathers J, Packard M, Alston L. Digital behaviour change interventions to increase vegetable intake in adults: a systematic review. International Journal of Behavioral Nutrition and Physical Activity 2023;20(1) View
  6. Brankovic A, Hendrie G, Baird D, Khanna S. Predicting Disengagement to Better Support Outcomes in a Web-Based Weight Loss Program Using Machine Learning Models: Cross-Sectional Study. Journal of Medical Internet Research 2023;25:e43633 View
  7. Mauch C, Golley R, Hendrie G. Variety Predicts Discretionary Food and Beverage Intake of Australian Adults: A Cross-Sectional Analysis of an Online Food Intake Survey. Journal of the Academy of Nutrition and Dietetics 2024;124(4):509 View
  8. Tran N, Leech R, Livingstone K, McNaughton S. Achieving high diet quality at eating occasions: findings from a nationally representative study of Australian adults. British Journal of Nutrition 2023:1 View
  9. Livingstone K, Rawstorn J, Alston L, Partridge S, Bastian A, Dullaghan K, McNaughton S, Hendrie G, Blekkenhorst L, Maddison R, Zhang Y, Barnett S, Mathers J, Godrich S. Co-design of a personalised digital intervention to improve vegetable intake in adults living in Australian rural communities. BMC Public Health 2024;24(1) View