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

A Mobile Phone Food Record App to Digitally Capture Dietary Intake for Adolescents in a Free-Living Environment: Usability Study

A Mobile Phone Food Record App to Digitally Capture Dietary Intake for Adolescents in a Free-Living Environment: Usability Study

A Mobile Phone Food Record App to Digitally Capture Dietary Intake for Adolescents in a Free-Living Environment: Usability Study

Journals

  1. Béjar L, García-Perea M, Reyes Ó, 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 View
  2. Kourkoutas Y, Chorianopoulos N, Nisiotou A, Valdramidis V, Karatzas K. Application of Innovative Technologies for Improved Food Quality and Safety. BioMed Research International 2016;2016:1 View
  3. Boushey C, Spoden M, Delp E, Zhu F, Bosch M, Ahmad Z, Shvetsov Y, DeLany J, Kerr D. Reported Energy Intake Accuracy Compared to Doubly Labeled Water and Usability of the Mobile Food Record among Community Dwelling Adults. Nutrients 2017;9(3):312 View
  4. Béjar L, Reyes Ó, García-Perea M. 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 View
  5. Eslick S, Jensen M, Collins C, Gibson P, Hilton J, Wood L. Characterising a Weight Loss Intervention in Obese Asthmatic Children. Nutrients 2020;12(2):507 View
  6. Ferri E, Galimberti A, Casiraghi M, Airoldi C, Ciaramelli C, Palmioli A, Mezzasalma V, Bruni I, Labra M. Towards a Universal Approach Based on Omics Technologies for the Quality Control of Food. BioMed Research International 2015;2015:1 View
  7. Bathgate K, Sherriff J, Leonard H, Dhaliwal S, Delp E, Boushey C, Kerr D. Feasibility of Assessing Diet with a Mobile Food  Record for Adolescents and Young Adults with  Down Syndrome. Nutrients 2017;9(3):273 View
  8. Segovia-Siapco G, Sabaté J. Using Personal Mobile Phones to Assess Dietary Intake in Free-Living Adolescents: Comparison of Face-to-Face Versus Telephone Training. JMIR mHealth and uHealth 2016;4(3):e91 View
  9. Amoutzopoulos B, Steer T, Roberts C, Cade J, Boushey C, Collins C, Trolle E, Boer E, Ziauddeen N, van Rossum C, Buurma E, Coyle D, Page P. Traditional methodsv.new technologies – dilemmas for dietary assessment in large-scale nutrition surveys and studies: a report following an international panel discussion at the 9th International Conference on Diet and Activity Methods (ICDAM9), Brisbane, 3 September 2015. Journal of Nutritional Science 2018;7 View
  10. Gonçalves R, Barreto D, Monteiro P, Zangeronimo M, Castelo P, van der Bilt A, Pereira L. Smartphone use while eating increases caloric ingestion. Physiology & Behavior 2019;204:93 View
  11. Reber E, Gomes F, Vasiloglou M, Schuetz P, Stanga Z. Nutritional Risk Screening and Assessment. Journal of Clinical Medicine 2019;8(7):1065 View
  12. Tay I, Garland S, Gorelik A, Wark J. Development and Testing of a Mobile Phone App for Self-Monitoring of Calcium Intake in Young Women. JMIR mHealth and uHealth 2017;5(3):e27 View
  13. Wahl D, Villinger K, König L, Ziesemer K, Schupp H, Renner B. Healthy food choices are happy food choices: Evidence from a real life sample using smartphone based assessments. Scientific Reports 2017;7(1) View
  14. Fowler L, Yingling L, Brooks A, Wallen G, Peters-Lawrence M, McClurkin M, Wiley Jr K, Mitchell V, Johnson T, Curry K, Johnson A, Graham A, Graham L, Powell-Wiley T. Digital Food Records in Community-Based Interventions: Mixed-Methods Pilot Study. JMIR mHealth and uHealth 2018;6(7):e160 View
  15. Chen Y, Wong J, Ayob A, Othman N, Poh B. Can Malaysian Young Adults Report Dietary Intake Using a Food Diary Mobile Application? A Pilot Study on Acceptability and Compliance. Nutrients 2017;9(1):62 View
  16. Dunn C, Turner-McGrievy G, Wilcox S, Hutto B. Dietary Self-Monitoring Through Calorie Tracking but Not Through a Digital Photography App Is Associated with Significant Weight Loss: The 2SMART Pilot Study—A 6-Month Randomized Trial. Journal of the Academy of Nutrition and Dietetics 2019;119(9):1525 View
  17. Wang J, Hsieh R, Tung Y, Chen Y, Yang C, Chen Y. Evaluation of a Technological Image-Based Dietary Assessment Tool for Children during Pubertal Growth: A Pilot Study. Nutrients 2019;11(10):2527 View
  18. Chib A, Lin S. Theoretical Advancements in mHealth: A Systematic Review of Mobile Apps. Journal of Health Communication 2018;23(10-11):909 View
  19. Fatehah A, Poh B, Shanita S, Wong J. Feasibility of Reviewing Digital Food Images for Dietary Assessment among Nutrition Professionals. Nutrients 2018;10(8):984 View
  20. Béjar L. 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 View
  21. Gunther C, Rogers C, Holloman C, Hopkins L, Anderson S, Miller C, Copeland K, Dollahite J, Pratt K, Webster A, Labyk A, Penicka C. Child diet and health outcomes of the simple suppers program: a 10-week, 2-group quasi-experimental family meals trial. BMC Public Health 2019;19(1) View
  22. Spruijt-Metz D, Wen C, Bell B, Intille S, Huang J, Baranowski T. Advances and Controversies in Diet and Physical Activity Measurement in Youth. American Journal of Preventive Medicine 2018;55(4):e81 View
  23. Beltran A, Dadabhoy H, Ryan C, Dholakia R, Jia W, Baranowski J, Sun M, Baranowski T. Dietary Assessment with a Wearable Camera among Children: Feasibility and Intercoder Reliability. Journal of the Academy of Nutrition and Dietetics 2018;118(11):2144 View
  24. Storey K. A changing landscape. Current Opinion in Clinical Nutrition and Metabolic Care 2015;18(5):437 View
  25. Bejar L, Sharp B, García-Perea M. The e-EPIDEMIOLOGY Mobile Phone App for Dietary Intake Assessment: Comparison with a Food Frequency Questionnaire. JMIR Research Protocols 2016;5(4):e208 View
  26. Warren J, Guelinckx I, Livingstone B, Potischman N, Nelson M, Foster E, Holmes B. Challenges in the assessment of total fluid intake in children and adolescents: a discussion paper. European Journal of Nutrition 2018;57(S3):43 View
  27. Boushey C, Spoden M, Zhu F, Delp E, Kerr D. New mobile methods for dietary assessment: review of image-assisted and image-based dietary assessment methods. Proceedings of the Nutrition Society 2017;76(3):283 View
  28. Burns K, McBride C, Patel B, FitzGerald G, Mathews S, Drennan J. Creating Consumer-Generated Health Data: Interviews and a Pilot Trial Exploring How and Why Patients Engage. Journal of Medical Internet Research 2019;21(6):e12367 View
  29. Ji Y, Plourde H, Bouzo V, Kilgour R, Cohen T. Validity and Usability of a Smartphone Image-Based Dietary Assessment App Compared to 3-Day Food Diaries in Assessing Dietary Intake Among Canadian Adults: Randomized Controlled Trial. JMIR mHealth and uHealth 2020;8(9):e16953 View
  30. 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
  31. Vasiloglou M, van der Horst K, Stathopoulou T, Jaeggi M, Tedde G, Lu Y, Mougiakakou S. The Human Factor in Automated Image-Based Nutrition Apps: Analysis of Common Mistakes Using the goFOOD Lite App. JMIR mHealth and uHealth 2021;9(1):e24467 View
  32. Naaman R, Parrett A, Bashawri D, Campo I, Fleming K, Nichols B, Burleigh E, Murtagh J, Reid J, Gerasimidis K. Assessment of Dietary Intake Using Food Photography and Video Recording in Free-Living Young Adults: A Comparative Study. Journal of the Academy of Nutrition and Dietetics 2021;121(4):749 View
  33. Höchsmann C, Martin C. Review of the validity and feasibility of image-assisted methods for dietary assessment. International Journal of Obesity 2020;44(12):2358 View
  34. Hoare J, Jebeile H, Garnett S, Lister N. Novel dietary interventions for adolescents with obesity: A narrative review. Pediatric Obesity 2021;16(9) View
  35. Jong S, Stevenson R, Winpenny E, Corder K, van Sluijs E. Recruitment and retention into longitudinal health research from an adolescent perspective: a qualitative study. BMC Medical Research Methodology 2023;23(1) View
  36. Caon M, Prinelli F, Angelini L, Carrino S, Mugellini E, Orte S, Serrano J, Atkinson S, Martin A, Adorni F. PEGASO e-Diary: User Engagement and Dietary Behavior Change of a Mobile Food Record for Adolescents. Frontiers in Nutrition 2022;9 View
  37. Muzenda T, Kamkuemah M, Battersby J, Oni T. Assessing adolescent diet and physical activity behaviour, knowledge and awareness in low- and middle-income countries: a systematised review of quantitative epidemiological tools. BMC Public Health 2022;22(1) View
  38. Zuppinger C, Taffé P, Burger G, Badran-Amstutz W, Niemi T, Cornuz C, Belle F, Chatelan A, Paclet Lafaille M, Bochud M, Gonseth Nusslé S. Performance of the Digital Dietary Assessment Tool MyFoodRepo. Nutrients 2022;14(3):635 View
  39. Idris G, Smith C, Galland B, Taylor R, Robertson C, Farella M. Home-Based Monitoring of Eating in Adolescents: A Pilot Study. Nutrients 2021;13(12):4354 View
  40. Van Wymelbeke-Delannoy V, Juhel C, Bole H, Sow A, Guyot C, Belbaghdadi F, Brousse O, Paindavoine M. A Cross-Sectional Reproducibility Study of a Standard Camera Sensor Using Artificial Intelligence to Assess Food Items: The FoodIntech Project. Nutrients 2022;14(1):221 View
  41. Ploderer B, Rezaei Aghdam A, Burns K. Patient-Generated Health Photos and Videos Across Health and Well-being Contexts: Scoping Review. Journal of Medical Internet Research 2022;24(4):e28867 View
  42. Tanweer A, Khan S, Mustafa F, Imran S, Humayun A, Hussain Z. Improving dietary data collection tools for better nutritional assessment – A systematic review. Computer Methods and Programs in Biomedicine Update 2022;2:100067 View
  43. Ramírez-Contreras C, Farran-Codina A, Zerón-Rugerio M, Izquierdo-Pulido M. Relative Validity and Reliability of the Remind App as an Image-Based Method to Assess Dietary Intake and Meal Timing in Young Adults. Nutrients 2023;15(8):1824 View
  44. 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
  45. Ghosh T, Han Y, Raju V, Hossain D, McCrory M, Higgins J, Boushey C, Delp E, Sazonov E. Integrated image and sensor-based food intake detection in free-living. Scientific Reports 2024;14(1) View

Books/Policy Documents

  1. Galhotra R. Nutrients in Dairy and their Implications on Health and Disease. View
  2. Thompson F, Subar A. Nutrition in the Prevention and Treatment of Disease. View
  3. Konishi T, Nagata M, Honjo M, Yoneyama A, Kurokawa M, Mishima K. Persuasive Technology: Development of Persuasive and Behavior Change Support Systems. View
  4. de Moraes Lopes M, Ferreira D, Ferreira A, da Silva G, Caetano A, Braz V. Artificial Intelligence in Precision Health. View
  5. Mao R, He J, Shao Z, Yarlagadda S, Zhu F. Pattern Recognition. ICPR International Workshops and Challenges. View