Published on in Vol 3, No 1 (2015): Jan-Mar

Diet App Use by Sports Dietitians: A Survey in Five Countries

Diet App Use by Sports Dietitians: A Survey in Five Countries

Diet App Use by Sports Dietitians: A Survey in Five Countries

Journals

  1. Braz V, Lopes M. Evaluation of mobile applications related to nutrition. Public Health Nutrition 2018:1 View
  2. Li K, White F, Tipoe T, Liu T, Wong M, Jesuthasan A, Baranchuk A, Tse G, Yan B. The Current State of Mobile Phone Apps for Monitoring Heart Rate, Heart Rate Variability, and Atrial Fibrillation: Narrative Review. JMIR mHealth and uHealth 2019;7(2):e11606 View
  3. Wardenaar F, Hoogervorst D, van der Burg N, Versteegen J, Yoo W, Tasevska N. Validity of a Food and Fluid Exercise Questionnaire for Macronutrient Intake during Exercise against Observations. Nutrients 2019;11(10):2391 View
  4. Chen J, Lieffers J, Bauman A, Hanning R, Allman‐Farinelli M. The use of smartphone health apps and other mobile health (mHealth) technologies in dietetic practice: a three country study. Journal of Human Nutrition and Dietetics 2017;30(4):439 View
  5. Vasiloglou M, Christodoulidis S, Reber E, Stathopoulou T, Lu Y, Stanga Z, Mougiakakou S. What Healthcare Professionals Think of “Nutrition & Diet” Apps: An International Survey. Nutrients 2020;12(8):2214 View
  6. Al Mheid I, Kelli H, Ko Y, Hammadah M, Ahmed H, Hayek S, Vaccarino V, Ziegler T, Gibson G, Lampl M, Alexander R, Brigham K, Martin G, Quyyumi A. Effects of a Health‐Partner Intervention on Cardiovascular Risk. Journal of the American Heart Association 2016;5(10) View
  7. Wang Q, Egelandsdal B, Amdam G, Almli V, Oostindjer M. Diet and Physical Activity Apps: Perceived Effectiveness by App Users. JMIR mHealth and uHealth 2016;4(2):e33 View
  8. Waldman H, Krings B, Basham S, Smith J, Fountain B, McAllister M. Effects of a 15-Day Low Carbohydrate, High-Fat Diet in Resistance-Trained Men. Journal of Strength and Conditioning Research 2018;32(11):3103 View
  9. Xie Z, Nacioglu A, Or C. Prevalence, Demographic Correlates, and Perceived Impacts of Mobile Health App Use Amongst Chinese Adults: Cross-Sectional Survey Study. JMIR mHealth and uHealth 2018;6(4):e103 View
  10. Régnier F, Dugré M, Darcel N, Adamiec C. Providing a Smart Healthy Diet for the Low-Income Population: Qualitative Study on the Usage and Perception of a Designed Cooking App. JMIR mHealth and uHealth 2018;6(11):e11176 View
  11. Régnier F, Adamiec C. Les outils numériques pour réduire la fracture alimentaire ? Étude sociologique de deux dispositifs à destination des catégories modestes. Cahiers de Nutrition et de Diététique 2019;54(6):326 View
  12. Jones A, Mitchell L, O'Connor R, Rollo M, Slater K, Williams L, Ball L. Investigating the Perceptions of Primary Care Dietitians on the Potential for Information Technology in the Workplace: Qualitative Study. Journal of Medical Internet Research 2018;20(10):e265 View
  13. Forster H, Walsh M, Gibney M, Brennan L, Gibney E. Personalised nutrition: the role of new dietary assessment methods. Proceedings of the Nutrition Society 2016;75(1):96 View
  14. Karduck J, Chapman-Novakofski K. Results of the Clinician Apps Survey, How Clinicians Working With Patients With Diabetes and Obesity Use Mobile Health Apps. Journal of Nutrition Education and Behavior 2018;50(1):62 View
  15. Heikkilä , Lehtovirta , Autio , Fogelholm , Valve . The Impact of Nutrition Education Intervention with and Without a Mobile Phone Application on Nutrition Knowledge Among Young Endurance Athletes. Nutrients 2019;11(9):2249 View
  16. 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 View
  17. Simpson A, Gemming L, Baker D, Braakhuis A. Do Image-Assisted Mobile Applications Improve Dietary Habits, Knowledge, and Behaviours in Elite Athletes? A Pilot Study. Sports 2017;5(3):60 View
  18. Régnier F, Chauvel L. Digital Inequalities in the Use of Self-Tracking Diet and Fitness Apps: Interview Study on the Influence of Social, Economic, and Cultural Factors. JMIR mHealth and uHealth 2018;6(4):e101 View
  19. Fallaize R, Zenun Franco R, Pasang J, Hwang F, Lovegrove J. Popular Nutrition-Related Mobile Apps: An Agreement Assessment Against a UK Reference Method. JMIR mHealth and uHealth 2019;7(2):e9838 View
  20. Khoury J, de Freitas A, Roque M, Albuquerque M, das Neves M, Garcia F, Jiménez-Murcia S. Assessment of the accuracy of a new tool for the screening of smartphone addiction. PLOS ONE 2017;12(5):e0176924 View
  21. Tam R, Beck K, Manore M, Gifford J, Flood V, O’Connor H. Effectiveness of Education Interventions Designed to Improve Nutrition Knowledge in Athletes: A Systematic Review. Sports Medicine 2019;49(11):1769 View
  22. Chen J, Berkman W, Bardouh M, Ng C, 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 View
  23. Mueller R. Exploring Family Nurse Practitioners' Practices in Recommending mHealth Apps to Patients. CIN: Computers, Informatics, Nursing 2020;38(2):71 View
  24. Xu X, Wang J, Hou L, Guo Z, Li J. A Dietary Management System Using Radio-Frequency Identification Technology to Collect Information on Chinese Food Consumption: Development and Feasibility Study. JMIR mHealth and uHealth 2018;6(8):e166 View
  25. Mobley C, Haun C, Roberson P, Mumford P, Romero M, Kephart W, Anderson R, Vann C, Osburn S, Pledge C, Martin J, Young K, Goodlett M, Pascoe D, Lockwood C, Roberts M. Effects of Whey, Soy or Leucine Supplementation with 12 Weeks of Resistance Training on Strength, Body Composition, and Skeletal Muscle and Adipose Tissue Histological Attributes in College-Aged Males. Nutrients 2017;9(9):972 View
  26. Ferrara G, Kim J, Lin S, Hua J, Seto E. A Focused Review of Smartphone Diet-Tracking Apps: Usability, Functionality, Coherence With Behavior Change Theory, and Comparative Validity of Nutrient Intake and Energy Estimates. JMIR mHealth and uHealth 2019;7(5):e9232 View
  27. Flaherty S, McCarthy M, Collins A, McAuliffe F. Can existing mobile apps support healthier food purchasing behaviour? Content analysis of nutrition content, behaviour change theory and user quality integration. Public Health Nutrition 2018;21(2):288 View
  28. Teixeira V, Voci S, Mendes‐Netto R, da Silva D. The relative validity of a food record using the smartphone application MyFitnessPal. Nutrition & Dietetics 2018;75(2):219 View
  29. 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 View
  30. Bouslimani A, Melnik A, Xu Z, Amir A, da Silva R, Wang M, Bandeira N, Alexandrov T, Knight R, Dorrestein P. Lifestyle chemistries from phones for individual profiling. Proceedings of the National Academy of Sciences 2016;113(48) View
  31. Cho J, Kim S. Personal and social predictors of use and non-use of fitness/diet app: Application of Random Forest algorithm. Telematics and Informatics 2020;55:101301 View
  32. Akdur G, Aydin M, Akdur G. Adoption of Mobile Health Apps in Dietetic Practice: Case Study of Diyetkolik. JMIR mHealth and uHealth 2020;8(10):e16911 View
  33. Raguzzini A, Toti E, Sciarra T, Fedullo A, Peluso I, Saso L. Cranberry for Bacteriuria in Individuals with Spinal Cord Injury: A Systematic Review and Meta-Analysis. Oxidative Medicine and Cellular Longevity 2020;2020:1 View
  34. Kelly J, Collins P, McCamley J, Ball L, Roberts S, Campbell K. Digital disruption of dietetics: are we ready?. Journal of Human Nutrition and Dietetics 2021;34(1):134 View
  35. Evenepoel C, Clevers E, Deroover L, Van Loo W, Matthys C, Verbeke K. Accuracy of Nutrient Calculations Using the Consumer-Focused Online App MyFitnessPal: Validation Study. Journal of Medical Internet Research 2020;22(10):e18237 View
  36. Che K, Qiu J, Yi L, Zou M, Li Z, Carr A, Snipe R, Benardot D. Effects of a Short-Term “Fat Adaptation with Carbohydrate Restoration” Diet on Metabolic Responses and Exercise Performance in Well-Trained Runners. Nutrients 2021;13(3):1033 View
  37. Shaw M, Satchell L, Thompson S, Harper E, Balsalobre-Fernández C, Peart D. Smartphone and Tablet Software Apps to Collect Data in Sport and Exercise Settings: Cross-sectional International Survey. JMIR mHealth and uHealth 2021;9(5):e21763 View
  38. Peart D, Briggs M, Shaw M. Mobile applications for the sport and exercise nutritionist: a narrative review. BMC Sports Science, Medicine and Rehabilitation 2022;14(1) View
  39. Tovar A, Richardson C, Keim N, Van Loan M, Davis B, Casazza G. Four Weeks of 16/8 Time Restrictive Feeding in Endurance Trained Male Runners Decreases Fat Mass, without Affecting Exercise Performance. Nutrients 2021;13(9):2941 View
  40. Slazus C, Ebrahim Z, Koen N. Mobile health apps: An assessment of needs, perceptions, usability, and efficacy in changing dietary choices. Nutrition 2022;101:111690 View
  41. Vaughan G, Prizeman G, Eustace-Cook J, Byrne G. Use of mHealth apps by nurses in the management of chronic wounds: a scoping review protocol. JBI Evidence Synthesis 2021;19(10):2783 View
  42. Yeh M, Lau W, Gong Z, Horlyck-Romanovsky M, Tung H, Zhu L, Ma G, Wylie-Rosett J. Development of a Web-Based Diabetes Prevention Program (DPP) for Chinese Americans: A Formative Evaluation Approach. International Journal of Environmental Research and Public Health 2022;20(1):599 View
  43. Dalakleidi K, Papadelli M, Kapolos I, Papadimitriou K. Applying Image-Based Food-Recognition Systems on Dietary Assessment: A Systematic Review. Advances in Nutrition 2022;13(6):2590 View
  44. Mohamed Kelli H, Witbrodt B, Shah A. The Future of Mobile Health Applications and Devices in Cardiovascular Health. EMJ Innovations 2017:92 View
  45. Samad S, Ahmed F, Naher S, Kabir M, Das A, Amin S, Islam S. Smartphone apps for tracking food consumption and recommendations: Evaluating artificial intelligence-based functionalities, features and quality of current apps. Intelligent Systems with Applications 2022;15:200103 View
  46. Régnier F. « Goût de liberté » et self-quantification. Réseaux 2018;n° 208-209(2):95 View
  47. Hinojosa-Nogueira D, Ortiz-Viso B, Navajas-Porras B, Pérez-Burillo S, González-Vigil V, de la Cueva S, Rufián-Henares J. Stance4Health Nutritional APP: A Path to Personalized Smart Nutrition. Nutrients 2023;15(2):276 View
  48. Venkataramanan R, Padhee S, Rao S, Kaoshik R, Sundara Rajan A, Sheth A. Ki-Cook: clustering multimodal cooking representations through knowledge-infused learning. Frontiers in Big Data 2023;6 View
  49. Ramaraj K, Narayan V, Dhivyaprabha T, Subashini P. A healthy nutrition suggestion model for indian women sports players & active youth using long short‐term memory. Internet Technology Letters 2023 View
  50. Ho D, Chiu W, Kao J, Tseng H, Yao C, Su H, Wei P, Le N, Nguyen H, Chang J. Mitigating errors in mobile-based dietary assessments: Effects of a data modification process on the validity of an image-assisted food and nutrition app. Nutrition 2023;116:112212 View

Books/Policy Documents

  1. Galhotra R. Nutrients in Dairy and their Implications on Health and Disease. View
  2. Giazitzi K, Karathanos V, Boskou G. Quality Assurance in the Era of Individualized Medicine. View
  3. de Moraes Lopes M, Ferreira D, Ferreira A, da Silva G, Caetano A, Braz V. Artificial Intelligence in Precision Health. View
  4. Ahmad M, Khan M, Bibi M, Ullah Z, Shah S. Mobile Devices and Smart Gadgets in Medical Sciences. View
  5. Xu X, Hou L, Guo Z, Wang J, Li J. Big Data – BigData 2018. View
  6. Sartori F, Shala K, Moglia A, Talpini J, Savi M. Metadata and Semantic Research. View