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

mHealth for Wellness, Behavior Change and Prevention (2743) Usability of Apps and User Perceptions of mHealth (899) Instruments and Questionnaires for Nutrition and Food Intake (159)

Published on in Vol 3, No 2 (2015): Apr-Jun

How Willing Are Adolescents to Record Their Dietary Intake? The Mobile Food Record

How Willing Are Adolescents to Record Their Dietary Intake? The Mobile Food Record

How Willing Are Adolescents to Record Their Dietary Intake? The Mobile Food Record

Authors of this article:

Carol Jo Boushey1 Author Orcid Image ;   Amelia J Harray2 Author Orcid Image ;   Deborah Anne Kerr2 Author Orcid Image ;   TusaRebecca E. Schap3 Author Orcid Image ;   Stacey Paterson4 Author Orcid Image ;   Tanisha Aflague1 Author Orcid Image ;   Marc Bosch Ruiz5 Author Orcid Image ;   Ziad Ahmad6 Author Orcid Image ;   Edward J Delp6 Author Orcid Image
Article Authors Cited by (45) Tweetations (17) Metrics

Journals

  1. Ahmed M, Oh A, Vanderlee L, Franco-Arellano B, Schermel A, Lou W, L’Abbé M. A randomized controlled trial examining consumers’ perceptions and opinions on using different versions of a FoodFlip© smartphone application for delivery of nutrition information. International Journal of Behavioral Nutrition and Physical Activity 2020;17(1) View
  2. 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
  3. Polfuss M, Moosreiner A, Boushey C, Delp E, Zhu F. Technology-Based Dietary Assessment in Youth with and Without Developmental Disabilities. Nutrients 2018;10(10):1482 View
  4. White B, Burns S, Giglia R, Scott J. Designing evaluation plans for health promotion mHealth interventions: a case study of the Milk Man mobile app. Health Promotion Journal of Australia 2016;27(3):198 View
  5. 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
  6. Chib A, Lin S. Theoretical Advancements in mHealth: A Systematic Review of Mobile Apps. Journal of Health Communication 2018;23(10-11):909 View
  7. 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
  8. Kim S, Martinović I, Katavić S. The use of mobile devices and applications for health information: A survey of Croatian students. Journal of Librarianship and Information Science 2020;52(3):880 View
  9. Halse R, Shoneye C, Pollard C, Jancey J, Scott J, Pratt I, Dhaliwal S, Norman R, Straker L, Boushey C, Delp E, Zhu F, Harray A, Szybiak M, Finch A, McVeigh J, Mullan B, Collins C, Mukhtar S, Edwards K, Healy J, Kerr D. Improving Nutrition and Activity Behaviors Using Digital Technology and Tailored Feedback: Protocol for the Tailored Diet and Activity (ToDAy) Randomized Controlled Trial. JMIR Research Protocols 2019;8(2):e12782 View
  10. 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
  11. Rangan A, O'Connor S, Giannelli V, Yap M, Tang L, Roy R, Louie J, Hebden L, Kay J, Allman-Farinelli M. Electronic Dietary Intake Assessment (e-DIA): Comparison of a Mobile Phone Digital Entry App for Dietary Data Collection With 24-Hour Dietary Recalls. JMIR mHealth and uHealth 2015;3(4):e98 View
  12. Bereznay M, Kopp C, Nyakwol A, Howe C. Promoting Food Literacy in Teens. Journal of Pediatric Nursing 2019;47:171 View
  13. 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
  14. White B, Martin A, White J, Burns S, Maycock B, Giglia R, Scott J. Theory-Based Design and Development of a Socially Connected, Gamified Mobile App for Men About Breastfeeding (Milk Man). JMIR mHealth and uHealth 2016;4(2):e81 View
  15. Badawy S, Thompson A, Liem R. Technology Access and Smartphone App Preferences for Medication Adherence in Adolescents and Young Adults With Sickle Cell Disease. Pediatric Blood & Cancer 2016;63(5):848 View
  16. Kerr D, Harray A, Pollard C, Dhaliwal S, Delp E, Howat P, Pickering M, Ahmad Z, Meng X, Pratt I, Wright J, Kerr K, Boushey C. The connecting health and technology study: a 6-month randomized controlled trial to improve nutrition behaviours using a mobile food record and text messaging support in young adults. International Journal of Behavioral Nutrition and Physical Activity 2016;13(1) View
  17. Ahn J, Song S, Moon S, Kim S, Lee J. The Perception of Laymen and Experts Toward Mobile Applications for Self-monitoring of Diet Based on in-depth Interviews and Focus Group Interviews. Korean Journal of Community Nutrition 2018;23(3):202 View
  18. Harray A, Boushey C, Pollard C, Panizza C, Delp E, Dhaliwal S, Kerr D. Perception v. actual intakes of junk food and sugar-sweetened beverages in Australian young adults: assessed using the mobile food record. Public Health Nutrition 2017;20(13):2300 View
  19. 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 View
  20. 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
  21. Spruijt-Metz D, Wen C, O’Reilly G, Li M, Lee S, Emken B, Mitra U, Annavaram M, Ragusa G, Narayanan S. Innovations in the Use of Interactive Technology to Support Weight Management. Current Obesity Reports 2015;4(4):510 View
  22. Ziesemer K, König L, Boushey C, Villinger K, Wahl D, Butscher S, Müller J, Reiterer H, Schupp H, Renner B. Occurrence of and Reasons for “Missing Events” in Mobile Dietary Assessments: Results From Three Event-Based Ecological Momentary Assessment Studies. JMIR mHealth and uHealth 2020;8(10):e15430 View
  23. 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
  24. Thompson F, Kirkpatrick S, Subar A, Reedy J, Schap T, Wilson M, Krebs-Smith S. The National Cancer Institute’s Dietary Assessment Primer: A Resource for Diet Research. Journal of the Academy of Nutrition and Dietetics 2015;115(12):1986 View
  25. Kerr D, Dhaliwal S, Pollard C, Norman R, Wright J, Harray A, Shoneye C, Solah V, Hunt W, Zhu F, Delp E, Boushey C. BMI is Associated with the Willingness to Record Diet  with  a  Mobile  Food  Record  among  Adults  Participating in Dietary Interventions. Nutrients 2017;9(3):244 View
  26. 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
  27. Hezarjaribi N, Mazrouee S, Hemati S, Chaytor N, Perrigue M, Ghasemzadeh H. Human-in-the-loop Learning for Personalized Diet Monitoring from Unstructured Mobile Data. ACM Transactions on Interactive Intelligent Systems 2019;9(4):1 View
  28. Wagner K, Braun E, Armah S, Horan D, Smith L, Pike J, Tu W, Hamilton M, Delp E, Campbell W, Boushey C, Hannon T, Gletsu-Miller N. Dietary Intervention for Glucose Tolerance In Teens (DIG IT): Protocol of a randomized controlled trial using health coaching to prevent youth-onset type 2 diabetes. Contemporary Clinical Trials 2017;53:171 View
  29. 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
  30. Shoneye C, Dhaliwal S, Pollard C, Boushey C, Delp E, Harray A, Howat P, Hutchesson M, Rollo M, Zhu F, Wright J, Pratt I, Jancey J, Halse R, Scott J, Mullan B, Collins C, Kerr D. Image-Based Dietary Assessment and Tailored Feedback Using Mobile Technology: Mediating Behavior Change in Young Adults. Nutrients 2019;11(2):435 View
  31. 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
  32. Szymczak H, Keller L, Debbeler L, Kollmann J, Lages N, Sproesser G, Gollwitzer P, Schupp H, Renner B. “I’m eating healthy now”: The relationship between perceived behavior change and diet. Food Quality and Preference 2021;89:104142 View
  33. 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
  34. Hattab S, Badrasawi M, Anabtawi O, Zidan S. Development and validation of a smartphone image-based app for dietary intake assessment among Palestinian undergraduates. Scientific Reports 2022;12(1) View
  35. Rounak , Pratiksha , Mrunal , Shweta . IoT Based Food Monitoring System. International Journal of Advanced Research in Science, Communication and Technology 2022:323 View
  36. Saronga N, Mosha I, Stewart S, Bakar S, Sunguya B, Burrows T, Leyna G, Adam M, Collins C, Rollo M. A Mixed-Method Study Exploring Experiences and Perceptions of Nutritionists Regarding Use of an Image-Based Dietary Assessment System in Tanzania. Nutrients 2022;14(3):417 View
  37. Lee H, Huang T, Yen L, Wu P, Chen K, Kung H, Liu C, Hsu C. Precision Nutrient Management Using Artificial Intelligence Based on Digital Data Collection Framework. Applied Sciences 2022;12(9):4167 View
  38. 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
  39. König L, Van Emmenis M, Nurmi J, Kassavou A, Sutton S. Characteristics of smartphone-based dietary assessment tools: a systematic review. Health Psychology Review 2022;16(4):526 View
  40. Arthurs N, Browne S, Boardman R, O'Donnell S, Doyle G, Kechadi T, Shahid A, Tully L, O’Malley G. Usability of BigO System in Pediatric Obesity Treatment: A Mixed-methods evaluation of clinical end-users. Computational and Structural Biotechnology Journal 2024 View

Books/Policy Documents

  1. Tilzey S, Stephens T, Patel S, Bunge E. The Encyclopedia of Child and Adolescent Development. View
  2. Thompson F, Subar A. Nutrition in the Prevention and Treatment of Disease. View
  3. Caon M, Carrino S, Prinelli F, Ciociola V, Adorni F, Lafortuna C, Tabozzi S, Serrano J, Condon L, Khaled O, Mugellini E. New Trends in Image Analysis and Processing -- ICIAP 2015 Workshops. View
  4. Johnson R, Kerr D, Schap T. Nutrition in the Prevention and Treatment of Disease. View